https://www.uni-weimar.de/kunst-und-gestaltung/wiki/api.php?action=feedcontributions&feedformat=atom&user=Fbonowski 2026-04-19T00:55:49Z User contributions MediaWiki 1.39.6 https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives&diff=93300 2017-10-20T15:55:35Z

<p>Fbonowski: </p> <hr /> <div>Für den Kurs mit dem selben Namen im SS 2017, siehe: [[GMU:Actors, Traces, Collectives/SS17]]<br /> <br /> Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 und 28.+29.10.2017 sowie Konsultationen&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 7b]], Seminarraum 204&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * Einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Links==<br /> Der Kurs ist in seinen Inhalten sehr ähnlich zu Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] [https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists].<br /> <br /> Ein gutes Tutorial für Einsteiger in Deutsch gibt es auf [http://www.creativecoding.org/ creativecoding.org]<br /> <br /> Beispielcode für sehr hübsch anzuschauende Grafikengibt es hier: [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> Eine große Liste mit Links gibt es hier:<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:WS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives&diff=93299 2017-10-20T15:45:20Z

<p>Fbonowski: </p> <hr /> <div>Für den Kurs mit dem selben Namen im SS 2017, siehe: [[GMU:Actors, Traces, Collectives/SS17]]<br /> <br /> Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 und 28.+29.10.2017 sowie Konsultationen&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 7b]], Seminarraum 204&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * Einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Links==<br /> Der Kurs ist in seinen Inhalten sehr ähnlich zu Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] [https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists].<br /> <br /> Ein gutes Tutorial für Einsteiger in Deutsch gibt es auf [http://www.creativecoding.org/]<br /> <br /> Beispielcode für sehr hübsch anzuschauende Grafikengibt es hier: [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> Eine große Liste mit Links gibt es hier:<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:WS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives&diff=93298 2017-10-20T15:44:36Z

<p>Fbonowski: </p> <hr /> <div>Für den Kurs mit dem selben Namen im SS 2017, siehe: [[GMU:Actors, Traces, Collectives/SS17]]<br /> <br /> Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 und 28.+29.10.2017 sowie Konsultationen&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 7b]], Seminarraum 204&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * Einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Links==<br /> Der Kurs ist in seinen Inhalten sehr ähnlich zu Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] [https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists].<br /> <br /> Ein gutes Tutorial für Einsteiger in Deutsch gibt es auf [http://www.creativecoding.org/]<br /> <br /> Beispielcode für sehr hübsch anzuschauende Grafikengibt es hier: [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> Eine große Liste mit Links gibt es hier:<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:WS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives&diff=93297 2017-10-20T15:33:51Z

<p>Fbonowski: </p> <hr /> <div>Für den Kurs mit dem selben Namen im SS 2017, siehe: [[GMU:Actors, Traces, Collectives/SS17]]<br /> <br /> Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 und 28.+29.10.2017 sowie Konsultationen&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 7b]], Seminarraum 204&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) oder JavaScript (P5.js) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * Einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Ablauf==<br /> Wir folgen grob ([) <br /> <br /> ==Links==<br /> Der Kurs ist in seinen Inhalten sehr ähnlich zu Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] [https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists].<br /> <br /> Ein gutes Tutorial für Einsteiger in Deutsch gibt es auf [http://www.creativecoding.org/]<br /> <br /> Beispielcode für sehr hübsch anzuschauende Grafikengibt es hier: [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> Eine große Liste mit Links gibt es hier:<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:WS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=Processing/Links&diff=93296 2017-10-20T15:25:19Z

<p>Fbonowski: </p> <hr /> <div>=== Processing ===<br /> * [http://www.processing.org Processing-Projekt]<br /> * [http://www.processingjs.org processing.js] Processing as [[JavaScript]] Port for [[HTML#HTML5|HTML5]] <br /> * [http://www.mobileprocessing.org mobile processing] Processing for [[JAVA]] enabled Mobile Phones<br /> * [http://www.luckybite.com/iprocessing iProcessing] Make iOS Apps from Processing Sketches<br /> * [http://procoding.audiocommander.de PR0C0D1N6] Processing on iOS<br /> <br /> ==== Processing in a Browser ====<br /> * [http://sketch.processing.org/ sketch.processing.org]''(with syntax coloring &amp; error console!)''<br /> * [http://sketchpad.cc sketchpad.cc] Cross-Browser Processing IDE<br /> * [http://www.processingjs.org/learning/ide processing.js IDE in a Browser] (may be combined with Pd for webaudio. Examples: [http://mccormick.cx/projects/WebPd/demos/Notes_Pad/Notes_Pad.html], [http://mccormick.cx/projects/WebPd/demos/processingjs-basic-example-with-audio])<br /> * [http://www.hascanvas.com hascanvas.com] Processing in a Browser <br /> * [http://jepstone.net/HiperPad HiperPad] Processing in a Mobile Browser<br /> <br /> === Learning Processing ===<br /> * [http://www.creativecoding.org Creative Coding wiki] Plattform für Gestalten mit Code von Jonas Loh, Steffen Fielder und Stephan Thiel<br /> * [http://www.generative-gestaltung.de Generative Gestaltung] - Webseite zum Buch mit vielen Beispielen und Ressourcen<br /> * [http://www.processing.org/learning Learning at processing.org]<br /> * [http://processing.org/reference/environment Processing Reference (IDE/Environment)]<br /> * [http://processing.org/reference Reference (API)]<br /> * [http://www.openprocessing.org Openprocessing, many Sketches with sources]<br /> * [http://btk.tillnagel.com Creative Coding 1 &amp; 2] Processing Kurs von Till Nagel / btk<br /> * [http://natureofcode.com The Nature of Code by Daniel Shifman]<br /> <br /> === Misc ===<br /> * [[Tracking Motion Detection#Processing]]<br /> * [http://rauldiazpoblete.com/project.php?p1=1&amp;p2=1&amp;lang=en Processing + Pure Data = Roland TR909]<br /> * [http://gombology.net A proposed toolbox/API for connecting synths like Pd to Apps like Processing]<br /> <br /> === Artists ===<br /> * [http://www.zugakousaku.com/index.html?en-prolab Beispiele von Futurismo Zugakousaku]<br /> * [http://reas.com Casey Reas]<br /> * [http://benfry.com Ben Fry]<br /> * [http://complexification.net Jared Tarbell]<br /> * [http://toxi.co.uk Karsten Schmidt]<br /> * [http://www.flight404.com Robert Hodgin]<br /> * [http://unlekker.net Marius Watz]<br /> * [http://www.maedastudio.com John Maeda]<br /> * [http://vimeo.com/7166047 Jonathan Bobrow]<br /> * https://beesandbombs.tumblr.com/<br /> * [http://thedotisblack.tumblr.com/ David Mrugala]<br /> <br /> === Communities ===<br /> * [https://www.tumblr.com/tagged/processing Tagged Processing on Tumblr]<br /> * [http://vimeo.com/groups/processing Vimeo Processing Group]<br /> <br /> === Literature ===<br /> {{ProcessingBooks}}<br /> <br /> [[Category:Processing]]<br /> [[Category:Linklist]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives/SS17/Funktionen&diff=93295 2017-10-20T15:21:33Z

<p>Fbonowski: </p> <hr /> <div>Einen Kreis gibt es in Processing nicht, daher machen wir uns einen aus einer Ellipse.<br /> (Minimalbeispiel einer eigenen Funktion)<br /> <br /> <br /> &lt;syntaxhighlight lang=&quot;javaScript&quot;&gt;<br /> void setup() {<br /> size(640,360);<br /> }<br /> <br /> void draw() {<br /> background(255);<br /> circle(200,200,40); // diese Funktion haben wir weiter unten selbst definiert<br /> }<br /> <br /> // hier definieren wir eine eigene Funktion fürs zeichnen von Kreisen.<br /> void circle(float xloc, float yloc, int size){<br /> //&quot;void&quot; bedeutet, dass die Funktion &quot;nichts&quot; zurückgibt<br /> // &quot;circle&quot; ist der name der Funktion<br /> // in den runden Klammern steht eine Liste von Daten, die wir der Funktion übergeben. Diese werden &quot;Argumente&quot; oder &quot;Parameter&quot; genannt.<br /> // für jeden Parameter wird jeweils ein Datentyp &quot;float&quot; und ein Name angegeben.<br /> // die Parameter erlauben es, den Code in der Funktion beim Aufruf flexibel mit Daten zu beschicken, die angeben, was konkret zu tun ist.<br /> //<br /> // in den geschweiften Klammern {} steht der Code, der ausgeführt wird, wenn die Funktion aufgerufen wird.<br /> <br /> ellipse(xloc,yloc,size,size);<br /> }<br /> <br /> &lt;/syntaxhighlight&gt;</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives/SS17/if_Bedingung&diff=93294 2017-10-20T15:16:34Z

<p>Fbonowski: </p> <hr /> <div>Hier testen wir, ob &quot;t&quot; gerade oder ungerade ist.<br /> &lt;syntaxhighlight lang=&quot;javaScript&quot;&gt;<br /> int t = 6;<br /> <br /> // das % Zeichen rechnet den ganzzahligen Rest einer Division des ersten Wertes durch den zweiten Wert aus.<br /> // also z.B. &quot;4 geteilt durch 2&quot; ==&gt; 2 rest 0 ==&gt; Gerade<br /> // Modulo ist sehr nützlich, um z.B. Ganze Zahlen auf einen bestimmten Wertebereich einzugrenzen (der Rest ist nie Größer als Der Divisor)<br /> // oder &quot;alle x Schritte&quot; etwas zu tun (wenn der der Schrittzahl %x ==0 ist)<br /> if(t % 2 == 0){ <br /> println(&quot;gerade&quot; + t);<br /> }else{<br /> println(&quot;ungerade&quot; + t);<br /> }<br /> &lt;/syntaxhighlight&gt;</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives&diff=92986 2017-10-06T11:21:48Z

<p>Fbonowski: </p> <hr /> <div>Für den Kurs mit dem selben Namen im SS 2017, siehe: [[GMU:Actors, Traces, Collectives/SS17]]<br /> <br /> Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 und 28.+29.10.2017 sowie Konsultationen&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 7b]], Seminarraum 204&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) oder JavaScript (P5.js) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Ablauf==<br /> Wir folgen grob Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] ([https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists]) und dem Buch [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> ==Links==<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:WS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives&diff=92985 2017-10-06T11:20:56Z

<p>Fbonowski: </p> <hr /> <div>Für den Kurs mit dem selben Namen im SS 2017, siehe: [[GMU:Actors, Traces, Collectives/SS17]]<br /> <br /> Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 und 28.+29.10.2017 sowie Konsultationen&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 5]], Seminarraum 204&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) oder JavaScript (P5.js) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Ablauf==<br /> Wir folgen grob Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] ([https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists]) und dem Buch [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> ==Links==<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:WS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives/SS17&diff=92685 2017-08-11T15:00:03Z

<p>Fbonowski: </p> <hr /> <div>Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 sowie 28.+29.10.2017 sowie Konsultationen&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 5]], Seminarraum 205&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) oder JavaScript (P5.js) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Ablauf==<br /> Wir folgen grob Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] ([https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists]) und dem Buch [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> ==Links==<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:SS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=Navigations:Sidebar&diff=92684 2017-08-11T14:53:27Z

<p>Fbonowski: </p> <hr /> <div>*[[Electroacoustic Composition]]<br /> **[[EKK:Start | Main Page ]]<br /> **Sites<br /> **[http://seam.hfm-weimar.de/ SeaM Blog ]<br /> **[http://seam.hfm-weimar.de/wiki Studio-Wiki ]<br /> **[http://seam.hfm-weimar.de/archiv Archive of Works ]<br /> **[[PDCON:Start | Pure Data Convention 2011 ]]<br /> <br /> *[[Experimental Radio]]<br /> **[[RADIO:Start | Startseite ]]<br /> **[[RADIO:Studio | Studios ]]<br /> <br /> *[[Experimental Television]]<br /> **[[EXPTV:Start | Startseite ]]<br /> <br /> *[[Media Environments]]<br /> **[[GMU:Start|Startseite ]]<br /> **[[GMU:Personen|Lecturers ]]<br /> **[[GMU:Works|Student works ]]<br /> **[[GMU:BFA MFA Finals|Graduate works ]]<br /> **Labs and Spaces<br /> **[[GMU:Performance Platform|Performance Platform ]]<br /> **[[GMU:DIY BioLab|DIY BioLab ]]<br /> **[[GMU:DIY Electronics Studio|DIY Electronics Studio ]]<br /> **Classes WS18<br /> **[[GMU:Artists Lab|Artists Lab ]]<br /> **[[GMU:DIY Biolab “Driver’s License”|DIY Biolab License ]]<br /> **[[GMU:Pd programming for humans and non-humans|Pd programming ]]<br /> **[[GMU:Actors, Traces, Collectives|Actors, Traces, Collectives]]<br /> **Classes SS17<br /> **[[GMU:Dinge, die träumen|Dinge, die träumen ]]<br /> **[[GMU:Artists Lab|Artists Lab ]]<br /> **[[GMU:(In)Visible Networks|(In)Visible Networks ]]<br /> **[[GMU:Board Games for Humans and Nonhumans|Board Games for Non.Humans ]]<br /> **[[GMU:Techniken des Virtuellen|Techniken des Virtuellen]]<br /> **[[GMU:The Hidden Layer: Artificial Intelligence in creative contexts|The Hidden Layer]]<br /> **[[GMU:Lebendige Spiele|Lebendige Spiele]]<br /> <br /> *[[Immersive Media]]<br /> **[[IMM:Start|Startseite ]]<br /> <br /> *[[Interface Design]]<br /> **[[IFD:Start|Startseite ]]<br /> **Kurse im SS 2017<br /> ** [[IFD:Bachelor-Grundlagen|Interface Design Grundlagen]]<br /> ** [[IFD:MasterclassSS17|Internationale Masterklasse]]<br /> ** [[IFD:MasterprojectSS17|Geolocalized Interfaces]]<br /> ** [[IFD:Printed_Electronics_ButtonUp|Button Up!]]<br /> ** [[IFD:Printed_Electronics_ElectronicUpcycling|Electronic Upcycling]]<br /> ** [[IFD:Computational_Thinking|Computational Thinking]]<br /> ** [[IFD:Wireless Communication of Things|Wireless Communication of Things]]<br /> ** [[IFD:Programming Interaction - Networked Things|Networked Things]]<br /> ** [[IFD:Kolloq_SS17|Kolloq]]<br /> **Kurse im WS 2016<br /> ** [[IFD:MasterprojectWS16|Advanced Interfaces: The Core]]<br /> ** [[IFD:Printed_Electronics_Inkjet|Electro-Papercraft]]'<br /> ** [[IFD:Printed_Electronics_Screenprint|Squeegee, brush, and multimeter]]<br /> ** [[IFD:TheNetworkIsTheMachine|The Network Is The Machine]]<br /> ** [[IFD:SpaceIsThePlace|Space Is The Place]]<br /> ** [[IFD:TangibleElectronics|Tangible Electronics]]<br /> ** [[IFD:ResearchingAndDesigning|Researching and Designing Interfaces]] <br /> ** [[IFD:ProgrammingInteraction|Programming Interaction]]<br /> ** [[IFD:Kolloq_WS16|Kolloq]]<br /> <br /> *[[Photo Workshops Media]]<br /> **[[FOTO:Start | Startseite ]]<br /> <br /> *[[Media Events]]<br /> **[[ME:Start | Startseite ]]<br /> **Medien-Ereignisse<br /> **[[ME:Studio_Bauhaus | Studio Bauhaus ]]<br /> <br /> *[[Moden &amp; öffentl. Erscheinungsbilder ]]<br /> **[[MODEN:Start | Startseite ]]<br /> **Work in Progress<br /> **[[MODEN:Moden_NMW | This is what we mean when we say ]]<br /> **Project Archive<br /> **[[MODEN:Project_Archive | Project Archive ]]<br /> **Media, Trend &amp; Public Appearance<br /> **[[MODEN:Events | Events ]]<br /> **[[MODEN:Personen | People ]]<br /> **[[MODEN:Inventory | Studios, Gear &amp; Props ]]<br /> <br /> *[[Multimedia storytelling]]<br /> **[[MME:Start | Startseite ]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=Navigations:Sidebar&diff=92683 2017-08-11T14:53:03Z

<p>Fbonowski: </p> <hr /> <div>*[[Electroacoustic Composition]]<br /> **[[EKK:Start | Main Page ]]<br /> **Sites<br /> **[http://seam.hfm-weimar.de/ SeaM Blog ]<br /> **[http://seam.hfm-weimar.de/wiki Studio-Wiki ]<br /> **[http://seam.hfm-weimar.de/archiv Archive of Works ]<br /> **[[PDCON:Start | Pure Data Convention 2011 ]]<br /> <br /> *[[Experimental Radio]]<br /> **[[RADIO:Start | Startseite ]]<br /> **[[RADIO:Studio | Studios ]]<br /> <br /> *[[Experimental Television]]<br /> **[[EXPTV:Start | Startseite ]]<br /> <br /> *[[Media Environments]]<br /> **[[GMU:Start|Startseite ]]<br /> **[[GMU:Personen|Lecturers ]]<br /> **[[GMU:Works|Student works ]]<br /> **[[GMU:BFA MFA Finals|Graduate works ]]<br /> **Labs and Spaces<br /> **[[GMU:Performance Platform|Performance Platform ]]<br /> **[[GMU:DIY BioLab|DIY BioLab ]]<br /> **[[GMU:DIY Electronics Studio|DIY Electronics Studio ]]<br /> **Classes WS18<br /> **[[GMU:Artists Lab|Artists Lab ]]<br /> **[[GMU:DIY Biolab “Driver’s License”|DIY Biolab License ]]<br /> **[[GMU:Pd programming for humans and non-humans|Pd programming ]]<br /> **[[GMU:Actors, Traces, Collectives|Actors, Traces, Collectives: Introduction to Processing]]<br /> **Classes SS17<br /> **[[GMU:Dinge, die träumen|Dinge, die träumen ]]<br /> **[[GMU:Artists Lab|Artists Lab ]]<br /> **[[GMU:(In)Visible Networks|(In)Visible Networks ]]<br /> **[[GMU:Board Games for Humans and Nonhumans|Board Games for Non.Humans ]]<br /> **[[GMU:Techniken des Virtuellen|Techniken des Virtuellen]]<br /> **[[GMU:The Hidden Layer: Artificial Intelligence in creative contexts|The Hidden Layer]]<br /> **[[GMU:Lebendige Spiele|Lebendige Spiele]]<br /> <br /> *[[Immersive Media]]<br /> **[[IMM:Start|Startseite ]]<br /> <br /> *[[Interface Design]]<br /> **[[IFD:Start|Startseite ]]<br /> **Kurse im SS 2017<br /> ** [[IFD:Bachelor-Grundlagen|Interface Design Grundlagen]]<br /> ** [[IFD:MasterclassSS17|Internationale Masterklasse]]<br /> ** [[IFD:MasterprojectSS17|Geolocalized Interfaces]]<br /> ** [[IFD:Printed_Electronics_ButtonUp|Button Up!]]<br /> ** [[IFD:Printed_Electronics_ElectronicUpcycling|Electronic Upcycling]]<br /> ** [[IFD:Computational_Thinking|Computational Thinking]]<br /> ** [[IFD:Wireless Communication of Things|Wireless Communication of Things]]<br /> ** [[IFD:Programming Interaction - Networked Things|Networked Things]]<br /> ** [[IFD:Kolloq_SS17|Kolloq]]<br /> **Kurse im WS 2016<br /> ** [[IFD:MasterprojectWS16|Advanced Interfaces: The Core]]<br /> ** [[IFD:Printed_Electronics_Inkjet|Electro-Papercraft]]'<br /> ** [[IFD:Printed_Electronics_Screenprint|Squeegee, brush, and multimeter]]<br /> ** [[IFD:TheNetworkIsTheMachine|The Network Is The Machine]]<br /> ** [[IFD:SpaceIsThePlace|Space Is The Place]]<br /> ** [[IFD:TangibleElectronics|Tangible Electronics]]<br /> ** [[IFD:ResearchingAndDesigning|Researching and Designing Interfaces]] <br /> ** [[IFD:ProgrammingInteraction|Programming Interaction]]<br /> ** [[IFD:Kolloq_WS16|Kolloq]]<br /> <br /> *[[Photo Workshops Media]]<br /> **[[FOTO:Start | Startseite ]]<br /> <br /> *[[Media Events]]<br /> **[[ME:Start | Startseite ]]<br /> **Medien-Ereignisse<br /> **[[ME:Studio_Bauhaus | Studio Bauhaus ]]<br /> <br /> *[[Moden &amp; öffentl. Erscheinungsbilder ]]<br /> **[[MODEN:Start | Startseite ]]<br /> **Work in Progress<br /> **[[MODEN:Moden_NMW | This is what we mean when we say ]]<br /> **Project Archive<br /> **[[MODEN:Project_Archive | Project Archive ]]<br /> **Media, Trend &amp; Public Appearance<br /> **[[MODEN:Events | Events ]]<br /> **[[MODEN:Personen | People ]]<br /> **[[MODEN:Inventory | Studios, Gear &amp; Props ]]<br /> <br /> *[[Multimedia storytelling]]<br /> **[[MME:Start | Startseite ]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives/SS17&diff=92682 2017-08-11T14:50:11Z

<p>Fbonowski: </p> <hr /> <div>Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 sowie 27.+28.2017&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 5]], Seminarraum 205&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> <br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) oder JavaScript (P5.js) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Ablauf==<br /> Wir folgen grob Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] ([https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists]) und dem Buch [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> ==Links==<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:SS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives/SS17&diff=92681 2017-08-11T14:49:57Z

<p>Fbonowski: </p> <hr /> <div>Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 sowie 27.+28.2017&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 5]], Seminarraum 205&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> [https://www.uni-weimar.de/qisserver/rds?state=verpublish&amp;status=init&amp;vmfile=no&amp;publishid=34713&amp;moduleCall=webInfo&amp;publishConfFile=webInfo&amp;publishSubDir=veranstaltung Im VLV]<br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) oder JavaScript (P5.js) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * einfache Grafikfunktionen in Processing<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]]<br /> ** for Schleifen<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Ablauf==<br /> Wir folgen grob Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] ([https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists]) und dem Buch [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> ==Links==<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:SS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Actors,_Traces,_Collectives/SS17&diff=92680 2017-08-11T14:48:35Z

<p>Fbonowski: </p> <hr /> <div>Einführung ins Programmieren anhand von graphischen Beispielen<br /> <br /> [[:Category:Werkmodul|Werkmodul]]&lt;br /&gt;<br /> ''Lehrender:'' [[Felix Bonowski]]&lt;br /&gt;<br /> ''Punkte:'' 6 [[ECTS]], 4 [[SWS]]&lt;br /&gt;<br /> ''Termine:''21.+22.10.2017 sowie 27.+28.2017&lt;br /&gt;<br /> ''Ort:'' [[Marienstraße 5]], Seminarraum 205&lt;br /&gt;<br /> ''Erstes Treffen:'' 21.10.2017 10:00&lt;br /&gt;<br /> [https://www.uni-weimar.de/qisserver/rds?state=verpublish&amp;status=init&amp;vmfile=no&amp;publishid=34713&amp;moduleCall=webInfo&amp;publishConfFile=webInfo&amp;publishSubDir=veranstaltung Im VLV]<br /> <br /> ==Kursbeschreibung==<br /> Anhand von aufeinander aufbauenden praktischen Übungen werden Grundkonzepte des Programmierens eingeführt.<br /> <br /> Die Übungsergebnisse sind überwiegend grafischer Natur und führen von einfachen Bewegungsspuren über L-Systeme und einer klassischen Schwarmsimulation (Craig Reynold's Boids) zur Live-Verarbeitung von Kameradaten.<br /> <br /> Die Veranstaltung wird Java (Processing) oder JavaScript (P5.js) verwenden.<br /> Kurssprache ist deutsch.<br /> Die Veranstaltung richtet sich primär an ProgrammieranfängerInnen<br /> <br /> Inhalte sind u.a.:<br /> <br /> * [[Punkt]]<br /> * Variablen<br /> * Kontrollstrukturen (If/Then/Else, Schleifen)<br /> ** [[/if Bedingung/]] und Abfrage ob gerade oder ungerade (Modulo)<br /> * [[/Funktionen/]]<br /> * Grundlagen Objektorientierung<br /> * [[/Agentensysteme/]]<br /> * Grundlagen Rekursion<br /> * Grundlagen Lineare Algebra für Grafikprogrammierung<br /> * Einfachste Algorithmen ([[wikipedia:de:Bubblesort|Bubblesort]])<br /> * [[/Tracking/]] von Bewegungen<br /> <br /> <br /> ==Ablauf==<br /> Wir folgen grob Daniel Shiffmans Buch [http://natureofcode.com/book/introduction/ The Nature of Code] ([https://www.youtube.com/user/shiffman/playlists?view=50&amp;sort=dd&amp;shelf_id=6 Kapitel video playlists]) und dem Buch [http://www.generative-gestaltung.de/code Generative Gestaltung]<br /> <br /> ==Links==<br /> [[Processing/Links]]<br /> <br /> [[Category:Werkmodul]]<br /> [[Category:SS17]]<br /> [[Category:Processing]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91292 2017-05-09T13:10:49Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> Word embeddings associate words with vectors in a high-dimensional space. Words that are close together in that space are more likely to occur in close proximity in a test than words which are far apart. See this article for details: [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> <br /> The whole process goes through a number of stages:<br /> <br /> === 1. Text corpus ===<br /> This is the raw data used for learning. Determines language, the topics that are covered and the semantics.<br /> Typical sources are Wikipedia and news articles.<br /> <br /> === 2. Tokens ===<br /> The corpus is split into words. These might be processed further, i.e. to clean up junk, or taking flections (i.e. verb forms) into account. <br /> <br /> === 3. Contexts ===<br /> The words are grouped into contexts. These might be all words in a sentence, a certain number of words in a neighborhood (aka. &quot;bag of words&quot;) or words that somehow relate to each other gramatically (as in &quot;dependency based word embeddings&quot; [https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/]).<br /> <br /> === 4. The algorithm ===<br /> Different algorithms can be used to map the relationship between words and their context into a vector space. The main contesters are...<br /> * '''Word2vec''' by Google, uses Neural Networks<br /> * '''Fastword''' by Facebook based on word2vec. Splits words into smaller particles in order to capture capturing syntactic relations (like apparent --&gt; apparently). Explained here: [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]. Needs a lot of memory.<br /> * '''GloVe''' by the Natural language processing group in standford [https://nlp.stanford.edu/projects/glove/]. Uses more conventional math instead of Neural Network &quot;Black Magic&quot; [https://www.quora.com/How-is-GloVe-different-from-word2vec].<br /> <br /> The different algorithms seem to perform quite similar, and results depend on the benchmark and training data. Word2Vec seems to be a little less memory hungry, though.<br /> === 5. Keyed Vecors ===<br /> <br /> Here comes the '''Good news''': All of the algorithms provide a table with words and and their positions in vector space... So '''all you need is that table'''!<br /> <br /> Fastvec is special in beeing able to match also on words that it hasn't seen before... but we probably don't even need that...<br /> <br /> ==== pre trained models ====<br /> Here is a collection of Words-&gt;Vector tables (&quot;models&quot;) that other people have created from big corpuses. This is what you probably want:<br /> <br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter, '''a good mix''']<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, '''Multiple languages''', no english, trained on Wikipedia]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia, HUGE files]<br /> * [https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/ https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/ an interesting approach that gives similarities between syntaktically equivalent words]<br /> <br /> In order to convert from GloVe to Word2Vec tables, the following script can be used:<br /> [[https://radimrehurek.com/gensim/scripts/glove2word2vec.html]]<br /> <br /> == Installation + getting started: ==<br /> <br /> ==Word2vec==<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]&lt;br&gt;<br /> <br /> Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]<br /> <br /> ==GloVe==<br /> Invented by the Natural language processing group in standford [https://nlp.stanford.edu/projects/glove/]. Uses more conventional math instead of Neural Network &quot;Black Magic&quot; [https://www.quora.com/How-is-GloVe-different-from-word2vec]. Seems to perform just slightly less well than Word2vec and FastWord.</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91274 2017-05-08T18:59:41Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> Word embeddings associate words with vectors in a high-dimensional space. Words that are close together in that space are more likely to occur in close proximity in a test than words which are far apart. See this article for details: [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> <br /> The whole process goes through a number of stages:<br /> <br /> === 1. The text corpus ===<br /> This is the raw data used for learning. Determines language, the topics that are covered and the semantics.<br /> Typical sources are Wikipedia and news articles.<br /> === 2. The tokens ===<br /> The corpus is split into words. These might be processed further, i.e. to clean up junk, or taking flections (i.e. verb forms) into account. <br /> === 3. Contexts ===<br /> The words are grouped into contexts. These might be all words in a sentence, a certain number of words in a neighborhood or words that somehow relate to each other gramatically (as in &quot;dependency based word embeddings&quot; [https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/]).<br /> === 4. The algorithm ===<br /> Different algorithms can be used to map the relationship between words and their context into a vector space. The main contesters are...<br /> * '''Word2vec''' by Google, uses Neural Networks<br /> * '''FastwordMade''' by Facebook based on word2vec. Splits words into smaller particles in order to capture capturing syntactic relations (like apparent ---&gt; apparently). Explained here: [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]<br /> * '''GloVe''' by the Natural language processing group in standford [https://nlp.stanford.edu/projects/glove/]. Uses more conventional math instead of Neural Network &quot;Black Magic&quot; [https://www.quora.com/How-is-GloVe-different-from-word2vec]. Seems to perform just slightly less well than Word2vec and FastWord.<br /> <br /> <br /> == Installation + getting started: ==<br /> <br /> ==Word2vec==<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]&lt;br&gt;<br /> <br /> Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]<br /> <br /> ==GloVe==<br /> Invented by the Natural language processing group in standford [https://nlp.stanford.edu/projects/glove/]. Uses more conventional math instead of Neural Network &quot;Black Magic&quot; [https://www.quora.com/How-is-GloVe-different-from-word2vec]. Seems to perform just slightly less well than Word2vec and FastWord.<br /> <br /> == pre trained models ==<br /> <br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]<br /> * [https://radimrehurek.com/gensim/scripts/glove2word2vec.html https://radimrehurek.com/gensim/scripts/glove2word2vec.html convert between GloVe and Word2Vec Format]<br /> * [https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/ https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/ an interesting approach that gives similarities between syntaktically equivalent words]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91268 2017-05-08T17:53:16Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> <br /> As wordvector algorithms <br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]&lt;br&gt;<br /> <br /> Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]<br /> <br /> ==GloVe==<br /> Invented by the Natural language processing group in standford [https://nlp.stanford.edu/projects/glove/]. Uses more conventional math instead of Neural Network &quot;Black Magic&quot; [https://www.quora.com/How-is-GloVe-different-from-word2vec]. Seems to perform just slightly less well than Word2vec and FastWord.<br /> <br /> == pre trained models ==<br /> <br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]<br /> * [https://radimrehurek.com/gensim/scripts/glove2word2vec.html https://radimrehurek.com/gensim/scripts/glove2word2vec.html convert between GloVe and Word2Vec Format]<br /> * [https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/ https://levyomer.wordpress.com/2014/04/25/dependency-based-word-embeddings/ an interesting approach that gives similarities between syntaktically equivalent words]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91245 2017-05-08T11:35:59Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]&lt;br&gt;<br /> <br /> Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]<br /> <br /> ==GloVe==<br /> Invented by the Natural language processing group in standford [https://nlp.stanford.edu/projects/glove/]. Uses more conventional math instead of Neural Network &quot;Black Magic&quot; [https://www.quora.com/How-is-GloVe-different-from-word2vec]. Seems to perform just slightly less well than Word2vec and FastWord.<br /> <br /> == pre trained models ==<br /> <br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91244 2017-05-08T11:28:51Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]&lt;br&gt;<br /> <br /> Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory<br /> <br /> === Installation + getting started: ===<br /> Included in the ''gensim'' package.<br /> <br /> To install, just type <br /> <br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> <br /> into a command window.<br /> <br /> Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]<br /> <br /> ==GloVe==<br /> Invented by the Natural language processing group in standford. [https://nlp.stanford.edu/projects/glove/]Uses more conventional math instead of Neural Network &quot;Black Magic&quot;. Seems to perform very slightly less well than Word2vec and FastWord.<br /> <br /> == pre trained models ==<br /> <br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91243 2017-05-08T11:27:18Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> <br /> === Installation + getting started: ===<br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]&lt;br&gt;<br /> <br /> Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory<br /> <br /> === Installation + getting started: ===<br /> Included in Gensim. Couldn't test yet due to memory constraints.<br /> Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]<br /> <br /> ==GloVe==<br /> Invented by the Natural language processing group in standford. [https://nlp.stanford.edu/projects/glove/]Uses more conventional math instead of Neural Network &quot;Black Magic&quot;. Seems to perform very slightly less well than Word2vec and FastWord.<br /> <br /> == pre trained models ==<br /> <br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91242 2017-05-08T10:10:24Z

<p>Fbonowski: /* Fastword */</p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> === Installation + getting started: ===<br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebbok based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]&lt;br&gt;<br /> <br /> Pretrained model files are HUGE<br /> <br /> ==GloVe==<br /> <br /> == pre trained models ==<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91241 2017-05-08T10:09:35Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> === Installation + getting started: ===<br /> &lt;code&gt;pip install gensim&lt;/code&gt;&lt;br&gt;<br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]&lt;br&gt;<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebbok based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]<br /> Pretrained model files are HUGE<br /> <br /> ==GloVe==<br /> <br /> == pre trained models ==<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91240 2017-05-08T10:08:52Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> === Installation + getting started: ===<br /> &lt;code&gt;pip install gensim&lt;/code&gt;\\<br /> Here are some of the things you can do with the model: [http://textminingonline.com/getting-started-with-word2vec-and-glove-in-python]\\<br /> Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].<br /> ==Fastword==<br /> Made by Facebbok based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]<br /> Pretrained model files are HUGE<br /> <br /> ==GloVe==<br /> <br /> == pre trained models ==<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91239 2017-05-08T09:55:04Z

<p>Fbonowski: </p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> === Installation + getting started: ===<br /> &lt;code&gt;pip install gensim&lt;/code&gt;<br /> <br /> ==Fastword==<br /> Made by Facebbok based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]<br /> Pretrained model files are HUGE<br /> <br /> ==GloVe==<br /> <br /> == pre trained models ==<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91238 2017-05-08T09:53:18Z

<p>Fbonowski: /* Word embeddings */</p> <hr /> <div><br /> == General Information on word embeddings ==<br /> For a general explanation look here:<br /> [https://blog.acolyer.org/2016/04/21/the-amazing-power-of-word-vectors/]<br /> ==Word2vec==<br /> Made by Google, uses Neural Net, performs good on semantics.<br /> === Installation + getting started: ===<br /> pip install gensim<br /> <br /> ==Fastword==<br /> Made by Facebbok based on word2vec. Better at capturing syntactic relations (like apparent ---&gt; apparently) see here:<br /> [https://rare-technologies.com/fasttext-and-gensim-word-embeddings/]<br /> Pretrained model files are HUGE<br /> <br /> ==GloVe==<br /> <br /> == pre trained models ==<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91237 2017-05-08T09:41:43Z

<p>Fbonowski: </p> <hr /> <div><br /> == Word embeddings ==<br /> <br /> === pre trained models ===<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> * [https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md https://github.com/facebookresearch/fastText/blob/master/pretrained-vectors.md: Fasttext, all imaginable languages, trained on Wikipedia]<br /> <br /> ===Word2vec===<br /> ===GloVe===<br /> ===Fastword===</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91236 2017-05-08T09:37:46Z

<p>Fbonowski: </p> <hr /> <div><br /> == Word embeddings ==<br /> <br /> === pre trained models ===<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> * [https://github.com/3Top/word2vec-api#where-to-get-a-pretrained-models https://github.com/3Top/word2vec-api Mostly GloVe, some word2vec, English, Trained on News, Wikipedia, Twitter]<br /> <br /> ===Word2vec===<br /> ===GloVe===<br /> ===Fastword===</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91235 2017-05-08T09:35:01Z

<p>Fbonowski: </p> <hr /> <div><br /> == Word embeddings ==<br /> <br /> === pre trained models ===<br /> * [https://github.com/Kyubyong/wordvectors https://github.com/Kyubyong/wordvectors: Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> <br /> ===Word2vec===<br /> ===GloVe===<br /> ===Fastword===</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91234 2017-05-08T09:34:35Z

<p>Fbonowski: </p> <hr /> <div><br /> == Word embeddings ==<br /> <br /> === pre trained models ===<br /> [https://github.com/Kyubyong/wordvectors Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]<br /> <br /> ===Word2vec===<br /> ===GloVe===<br /> ===Fastword===</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91233 2017-05-08T09:33:55Z

<p>Fbonowski: </p> <hr /> <div><br /> == Word embeddings ==<br /> <br /> === pre trained models ===<br /> [[https://github.com/Kyubyong/wordvectors|Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]]<br /> <br /> ===Word2vec===<br /> ===GloVe===<br /> ===Fastword===</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91232 2017-05-08T09:33:41Z

<p>Fbonowski: </p> <hr /> <div><br /> == Word embeddings ==<br /> <br /> === pre trained models<br /> [[https://github.com/Kyubyong/wordvectors|Word2Vec and FastText, Multiple languages, no english, trained on Wikipedia]]<br /> <br /> ===Word2vec===<br /> ===GloVe===<br /> ===Fastword===</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:Topics&diff=91231 2017-05-08T09:01:40Z

<p>Fbonowski: Created page with &quot; == Word embeddings == ===Word2vec=== ===GloVe=== ===Fastword===&quot;</p> <hr /> <div><br /> == Word embeddings ==<br /> ===Word2vec===<br /> ===GloVe===<br /> ===Fastword===</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:_Artificial_Intelligence_in_creative_contexts&diff=91230 2017-05-08T08:54:46Z

<p>Fbonowski: </p> <hr /> <div>=The Hidden Layer=<br /> Artificial Intelligence in creative contexts.<br /> <br /> == Links and Topics ==<br /> [[GMU:The_Hidden_Layer:Topics]]<br /> ==Formalities==<br /> ''Lecturer:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br&gt;<br /> ''Credits:'' 6 [[ECTS]], 4 [[SWS]]&lt;br&gt;<br /> ''Date:''Wednesday 9:15-12:30&lt;br&gt;<br /> ''Venue:'' Raum 204, Marienstrasse 7&lt;br&gt;<br /> ''Eglible participants:'' BfA MKG, MfA MKG, VK, Media Architecture, PD, Diplom Kunst&lt;br&gt;<br /> ''First meeting:'' Wednesday, 12th of April 9:15-12:30&lt;br&gt;<br /> <br /> ==Application==<br /> We participate in the '''Zentrale Projektvergabe der Fakultät Kunst und Gestaltung.'''&lt;br&gt;<br /> So please... '''Come to the &quot;Projektbörse&quot; on Monday, 3. April 11:00-12.30 in Audimax'''<br /> <br /> Preference will be given to those who &quot;win&quot; a place there, everybody else is welcome if there is still capacity.<br /> <br /> <br /> ==Course content==<br /> ''How does the world look like if you happen to be an artificial intelligence?''<br /> <br /> ''What's going on when machines cathegorize sensual information?''&lt;br /&gt;<br /> ''What's their inner model of the world?''&lt;br /&gt;<br /> ''How do they make decisions?''&lt;br /&gt;<br /> ''How can they express themselves?''&lt;br /&gt;<br /> <br /> ''Are their intentions benign?''<br /> <br /> <br /> During the course, we will collect our own data and use classical machine learning algorithms to develop an understanding for a datadriven perspective on the world.<br /> <br /> The focus will be put on cathegorizing and generating images, texts and sound.<br /> <br /> As part of your exercises you will conduct measurements, do research and apply algorithms that were presented during the course.<br /> <br /> Programming experience is welcome - if you don't have any, but you bring a lot of interest for the topic, you can form a team with other participants with more technical know how.</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organization&diff=91069 2017-05-02T10:06:21Z

<p>Fbonowski: </p> <hr /> <div>== Tasks/ToDo==<br /> <br /> === Design of physical environment for the ants ===<br /> ==== Breeding/Nest/Life support====<br /> * Matthias<br /> * Maud<br /> ==== Game Landscape====<br /> * Maike<br /> * Maud<br /> * René<br /> <br /> * Materials<br /> [[GMU:Lebendige_Spiele:Organization:Landscape]]<br /> === Camera Tracking ===<br /> * Matthias<br /> * Joachim<br /> * Yorrick<br /> [[GMU:Lebendige_Spiele:Organization:Tracking]]<br /> <br /> <br /> === Game Mechanism===<br /> * Scale of Landscape<br /> ==== Graphics/Visualization Virtual ====<br /> * Yorrick<br /> * Dominik<br /> [[GMU:Lebendige_Spiele:Organization:Mechanisms_Virtual]]<br /> <br /> * Story<br /> * Goals<br /> * Information<br /> * Rules<br /> ==== Outside/webApp ====<br /> * Maud<br /> * Matthias<br /> <br /> * Story<br /> * Goals<br /> * Information<br /> * Rules<br /> [[GMU:Lebendige_Spiele:Organization:Mechanisms_Outside]]<br /> === Design &amp;Productionof the environment for the humans ===<br /> ==== Graphics/Visualization Virtual ====<br /> * Yorrick<br /> * René<br /> * Dominick<br /> * Joachim<br /> [[GMU:Lebendige_Spiele:Organization:Production_Virtual]]<br /> ==== Outside/webApp ====<br /> * Matthias<br /> <br /> <br /> [[GMU:Lebendige_Spiele:Organization:Production_Outside]]<br /> <br /> == Milestones ==<br /> Let's create a list of milestones here.<br /> For each of them write:<br /> <br /> === Success criteria (Replace this header with a brief description) ===<br /> * How can I tell this part is finished?<br /> === Diskuss ===<br /> * What needs to be discussed/agreed on?<br /> === Material ===<br /> * What needs to be bought/found/acquired in the course of making this?<br /> === Activities ===<br /> * What needs to be built/programmed/grown/written?<br /> === Risks and Plan B ===<br /> * Is there anything likely to go wrong?<br /> * What can we do about this in case of unexpected difficulties?<br /> === Time ===<br /> * How long will this take? (Workdays/Weeks)</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organization&diff=91068 2017-05-02T09:56:37Z

<p>Fbonowski: </p> <hr /> <div>== Tasks/ToDo==<br /> === Cathegory of what is todo===<br /> Who is responsible?<br /> <br /> === Design of physical environment for the ants ===<br /> ==== Life support====<br /> ==== Game Landscape====<br /> * Materials<br /> <br /> === Camera Tracking ===<br /> <br /> <br /> === Game Mechanism===<br /> * Scale of Landscape<br /> ==== Graphics/Visualization Virtual ====<br /> * Story<br /> * Goals<br /> ==== Outside/webApp ====<br /> * Story<br /> * Goals<br /> <br /> === Design of the environment for the humans ===<br /> ==== Decision: Virtual/Outise/Both ====<br /> <br /> ==== Graphics/Visualization Virtual ====<br /> ==== Outside/webApp ====<br /> <br /> <br /> <br /> == Milestones ==<br /> Let's create a list of milestones here.<br /> For each of them write:<br /> <br /> === Success criteria (Replace this header with a brief description) ===<br /> * How can I tell this part is finished?<br /> === Diskuss ===<br /> * What needs to be discussed/agreed on?<br /> === Material ===<br /> * What needs to be bought/found/acquired in the course of making this?<br /> === Activities ===<br /> * What needs to be built/programmed/grown/written?<br /> === Risks and Plan B ===<br /> * Is there anything likely to go wrong?<br /> * What can we do about this in case of unexpected difficulties?<br /> === Time ===<br /> * How long will this take? (Workdays/Weeks)</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organization&diff=90944 2017-04-25T07:05:11Z

<p>Fbonowski: Created page with &quot; == Milestones == Let&#039;s create a list of milestones here. For each of them write: === Success criteria (Replace this header with a brief description) === * How can I tell thi...&quot;</p> <hr /> <div><br /> == Milestones ==<br /> Let's create a list of milestones here.<br /> For each of them write:<br /> <br /> === Success criteria (Replace this header with a brief description) ===<br /> * How can I tell this part is finished?<br /> === Diskuss ===<br /> * What needs to be discussed/agreed on?<br /> === Material ===<br /> * What needs to be bought/found/acquired in the course of making this?<br /> === Activities ===<br /> * What needs to be built/programmed/grown/written?<br /> === Risks and Plan B ===<br /> * Is there anything likely to go wrong?<br /> * What can we do about this in case of unexpected difficulties?<br /> === Time ===<br /> * How long will this take? (Workdays/Weeks)</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele&diff=90941 2017-04-25T06:59:03Z

<p>Fbonowski: </p> <hr /> <div>=Spiele mit dem Lebendigen / Lebendige Spiele =<br /> Biogames: Playful interactions with the Living<br /> ==Formalities==<br /> ''Lecturer:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br&gt;<br /> ''Credits:'' 6 [[ECTS]], 4 [[SWS]]&lt;br&gt;<br /> ''Date:''Tuesday, 11:00-12:30 + 13:30-15:00&lt;br&gt;<br /> ''Venue:'' DIY Biolab + Raum 201, 204, Marienstrasse 7&lt;br&gt;<br /> ''Eglible participants:''BfA MKG, MfA MKG, VK, Freie Kunst, Media Architecture&lt;br&gt;<br /> ''First meeting:''Tuesday, 11th of April, 11:00-12:30 + 13:30-15:00&lt;br&gt;<br /> <br /> == Organisms ==<br /> We collect information about different organisms here:<br /> [[GMU:Lebendige_Spiele:Organisms|Organisms]]<br /> <br /> == Organization/Production ==<br /> We collect information about the production of our exhibit here:<br /> [[GMU:Lebendige_Spiele:Organization|Organization]]<br /> <br /> ==Course content==<br /> Living things occur in many games -but usually, they are either simulated, represented by dead matter or other human players.<br /> <br /> In this course, we will explore how living things can play a role in playful interactions.<br /> Students will develop a concept for an experimental game, set it up as a team and present in at an exhibition of a game conference in Düsseldorf.<br /> Practical skills such as microbiological lab-practice, electronics, image analysis, computer graphics and simple mechanics will be taught as needed.<br /> <br /> ===German Version===<br /> Das Lebendige kommt in vielen Spielen vor - seine Rolle wird jedoch meist mit toter Materie, Algorithmen oder menschlichen Mitspielern besetzt.<br /> <br /> Im Kurs wird ausgelotet, wie das Lebendige in Spiele mit einbezogen werden kann.<br /> Ein von den Studierenden erarbeiteter experimenteller Spielentwurf wird im Anschluss praktisch in der Gruppe umgesetzt und im Rahmen einer Ausstellung auf einer Konferenz präsentiert.<br /> Dazu werden je nach Bedarf und Interesse Techniken aus den Bereichen Mikrobiologie, Elektronik, Bildverarbeitung, Computergrafik und Mechanik vermittelt.</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90739 2017-04-18T09:08:37Z

<p>Fbonowski: </p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena (René)<br /> <br /> [[GMU:Lebendige_Spiele:Axolotl]] (Maike, Sarah)<br /> <br /> (Wild) Pigeons (René)<br /> <br /> [[GMU:Lebendige_Spiele:Ants]] (Maud, Sarah)<br /> <br /> [[GMU:Lebendige_Spiele:Snails]] ((Maud, Sarah, Julius)<br /> <br /> Bacteria (Maike)<br /> <br /> Slimemold (Dominik)<br /> <br /> Flies (Julius)<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;) (Yorrick, Joachim)<br /> <br /> Jellyfish (Sarah, Julius)<br /> <br /> Plants (Yorrick, Joachim)<br /> <br /> Rodents (Rats/Mice) (Dominik)<br /> <br /> Crickets (Grillen) (Maud)<br /> <br /> Midgets &quot;Larven&quot; <br /> <br /> [[GMU:Lebendige_Spiele:Beetles]] (Maike)<br /> <br /> == Cathegories==<br /> ===Sensing===<br /> * What do we have to do in order to see/feel/hear/smell them?<br /> * Is there any way to make them look particularly beautiful/interesting/intense?<br /> <br /> ===Communication===<br /> * What can we do in order to make them react to us?<br /> * How fast, how strong, how predictable is that reaction?<br /> <br /> ===Space===<br /> * Which kind of space would they work together well with?<br /> <br /> ===Signs===<br /> * What associations to you have to them? / Do they have any metaphoric value?<br /> <br /> ===Ethics/ Living Conditions===<br /> * What do we have to provide/avoid in order to treat them &quot;right&quot;?<br /> <br /> ===Logistics===<br /> * How can we get them? /How much do they cost?<br /> * Do we need any special equippment for them?<br /> * How long can we keep them?<br /> ** In an exhibition setting?<br /> ** In our lab?</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90724 2017-04-18T08:42:05Z

<p>Fbonowski: </p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena<br /> <br /> [[GMU:Lebendige_Spiele:Axolotl]]<br /> <br /> (Wild) Pigeons<br /> <br /> [[GMU:Lebendige_Spiele:Ants]]<br /> <br /> Snails<br /> <br /> Bacteria<br /> <br /> Slimemold<br /> <br /> Flies<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;)<br /> <br /> Jellyfish<br /> <br /> Plants<br /> <br /> Rodents (Rats/Mice)<br /> <br /> Crickets (Grillen)<br /> <br /> Midgets &quot;Larven&quot;<br /> <br /> [[GMU:Lebendige_Spiele:Beetles]]<br /> == Cathegories==<br /> ===Sensing===<br /> * What do we have to do in order to see/feel/hear/smell them?<br /> * Is there any way to make them look particularly beautiful/interesting/intense?<br /> <br /> ===Communication===<br /> * What can we do in order to make them react to us?<br /> * How fast, how strong, how predictable is that reaction?<br /> <br /> ===Space===<br /> * Which kind of space would they work together well with?<br /> <br /> ===Signs===<br /> * What associations to you have to them? / Do they have any metaphoric value?<br /> <br /> ===Ethics/ Living Conditions===<br /> * What do we have to provide/avoid in order to treat them &quot;right&quot;?<br /> <br /> ===Logistics===<br /> * How can we get them? /How much do they cost?<br /> * Do we need any special equippment for them?<br /> * How long can we keep them?<br /> ** In an exhibition setting?<br /> ** In our lab?</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90723 2017-04-18T08:41:41Z

<p>Fbonowski: /* Oranisms that can participate in a Game */</p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena<br /> <br /> [[GMU:Lebendige_Spiele:Axolotl]]<br /> <br /> (Wild) Pigeons<br /> <br /> [[GMU:Lebendige_Spiele:Ants]]<br /> <br /> Snails<br /> <br /> Bacteria<br /> <br /> Slimemold<br /> <br /> Flies<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;)<br /> <br /> Jellyfish<br /> <br /> Plants<br /> <br /> Rodents (Rats/Mice)<br /> <br /> Crickets (Grillen)<br /> <br /> Midgets &quot;Larven&quot;<br /> <br /> == Cathegories==<br /> ===Sensing===<br /> * What do we have to do in order to see/feel/hear/smell them?<br /> * Is there any way to make them look particularly beautiful/interesting/intense?<br /> <br /> ===Communication===<br /> * What can we do in order to make them react to us?<br /> * How fast, how strong, how predictable is that reaction?<br /> <br /> ===Space===<br /> * Which kind of space would they work together well with?<br /> <br /> ===Signs===<br /> * What associations to you have to them? / Do they have any metaphoric value?<br /> <br /> ===Ethics/ Living Conditions===<br /> * What do we have to provide/avoid in order to treat them &quot;right&quot;?<br /> <br /> ===Logistics===<br /> * How can we get them? /How much do they cost?<br /> * Do we need any special equippment for them?<br /> * How long can we keep them?<br /> ** In an exhibition setting?<br /> ** In our lab?<br /> <br /> [[GMU:Lebendige_Spiele:Beetles]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90722 2017-04-18T08:41:13Z

<p>Fbonowski: </p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena<br /> <br /> [[GMU:Lebendige_Spiele:Axolotl]]<br /> <br /> (Wild) Pigeons<br /> <br /> [[GMU:Lebendige_Spiele:Ants]]<br /> <br /> Snails<br /> <br /> Bacteria<br /> <br /> Slimemold<br /> <br /> Flies<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;)<br /> <br /> Jellyfish<br /> <br /> Plants<br /> <br /> Rodents (Rats/Mice)<br /> <br /> Midgets &quot;Larven&quot;<br /> <br /> == Cathegories==<br /> ===Sensing===<br /> * What do we have to do in order to see/feel/hear/smell them?<br /> * Is there any way to make them look particularly beautiful/interesting/intense?<br /> <br /> ===Communication===<br /> * What can we do in order to make them react to us?<br /> * How fast, how strong, how predictable is that reaction?<br /> <br /> ===Space===<br /> * Which kind of space would they work together well with?<br /> <br /> ===Signs===<br /> * What associations to you have to them? / Do they have any metaphoric value?<br /> <br /> ===Ethics/ Living Conditions===<br /> * What do we have to provide/avoid in order to treat them &quot;right&quot;?<br /> <br /> ===Logistics===<br /> * How can we get them? /How much do they cost?<br /> * Do we need any special equippment for them?<br /> * How long can we keep them?<br /> ** In an exhibition setting?<br /> ** In our lab?<br /> <br /> [[GMU:Lebendige_Spiele:Beetles]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90717 2017-04-18T08:28:09Z

<p>Fbonowski: </p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena<br /> <br /> [[GMU:Lebendige_Spiele:Axolotl]]<br /> <br /> (Wild) Pigeons<br /> <br /> [[GMU:Lebendige_Spiele:Ants]]<br /> <br /> Snails<br /> <br /> Bacteria<br /> <br /> Slimemold<br /> <br /> Flies<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;)<br /> <br /> Jellyfish<br /> <br /> Plants<br /> <br /> Rodents (Rats/Mice)<br /> <br /> == Cathegories==<br /> ===Sensing===<br /> * What do we have to do in order to see/feel/hear/smell them?<br /> * Is there any way to make them look particularly beautiful/interesting/intense?<br /> <br /> ===Communication===<br /> * What can we do in order to make them react to us?<br /> * How fast, how strong, how predictable is that reaction?<br /> <br /> ===Space===<br /> * Which kind of space would they work together well with?<br /> <br /> ===Signs===<br /> * What associations to you have to them? / Do they have any metaphoric value?<br /> <br /> ===Ethics/ Living Conditions===<br /> * What do we have to provide/avoid in order to treat them &quot;right&quot;?<br /> <br /> ===Logistics===<br /> * How can we get them? /How much do they cost?<br /> * Do we need any special equippment for them?<br /> * How long can we keep them?<br /> ** In an exhibition setting?<br /> ** In our lab?<br /> <br /> [[GMU:Lebendige_Spiele:Beetles]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90714 2017-04-18T08:20:05Z

<p>Fbonowski: </p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena<br /> <br /> [[GMU:Lebendige_Spiele:Axolotl]]<br /> <br /> (Wild) Pigeons<br /> <br /> [[GMU:Lebendige_Spiele:Ants]]<br /> <br /> Snails<br /> <br /> Bacteria<br /> <br /> Slimemold<br /> <br /> Flies<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;)<br /> <br /> Jellyfish<br /> <br /> Plants<br /> <br /> Rodents (Rats/Mice)<br /> <br /> == Cathegories==<br /> 1) Sensing<br /> What do we have to do in order to see/feel/hear/smell them?<br /> Is there any way to make them look particularly beautiful/interesting/intense?<br /> <br /> 2) Communication<br /> What can we do in order to make them react to us?<br /> How fast, how strong, how predictable is that reaction?<br /> <br /> 3) Space<br /> Which kind of space would they work together well with?<br /> <br /> 4) Signs<br /> What associations to you have to them? / Do they have any metaphoric value?<br /> <br /> 4) Ethics/ Living Conditions<br /> What do we have to provide/avoid in order to treat them &quot;right<br /> <br /> 5) Logistics <br /> How can we get them? /How much do they cost?<br /> Do we need any special equippment for them?<br /> How long can we keep them?<br /> In an exhibition setting?<br /> In our lab?<br /> <br /> [[GMU:Lebendige_Spiele:Beetles]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90713 2017-04-18T08:18:34Z

<p>Fbonowski: </p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena<br /> <br /> [[GMU:Lebendige_Spiele:Axolotl]]<br /> <br /> (Wild) Pigeons<br /> <br /> [[GMU:Lebendige_Spiele:Ants]]<br /> <br /> Snails<br /> <br /> Bacteria<br /> <br /> Slimemold<br /> <br /> Flies<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;)<br /> <br /> Jellyfish<br /> <br /> Plants<br /> <br /> Rodents (Rats/Mice)<br /> <br /> [[GMU:Lebendige_Spiele:Beetles]]</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90710 2017-04-18T08:15:19Z

<p>Fbonowski: </p> <hr /> <div>== Oranisms that can participate in a Game ==<br /> <br /> Euglena<br /> <br /> Axolotl<br /> <br /> (Wild) Pigeons<br /> <br /> Ants<br /> <br /> Snails<br /> <br /> Bacteria<br /> <br /> Slimemold<br /> <br /> Flies<br /> <br /> Artemia salina (Sea monkey/&quot;Yps urzeitkrebs&quot;)<br /> <br /> Jellyfish<br /> <br /> Plants<br /> <br /> Rodents (Rats/Mice)</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele:Organisms&diff=90707 2017-04-18T06:52:04Z

<p>Fbonowski: Created page with &quot; == Oranisms that can participate in a Game ==&quot;</p> <hr /> <div><br /> == Oranisms that can participate in a Game ==</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele&diff=90706 2017-04-18T06:51:29Z

<p>Fbonowski: </p> <hr /> <div>=Spiele mit dem Lebendigen / Lebendige Spiele =<br /> Biogames: Playful interactions with the Living<br /> ==Formalities==<br /> ''Lecturer:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br&gt;<br /> ''Credits:'' 6 [[ECTS]], 4 [[SWS]]&lt;br&gt;<br /> ''Date:''Tuesday, 11:00-12:30 + 13:30-15:00&lt;br&gt;<br /> ''Venue:'' DIY Biolab + Raum 201, 204, Marienstrasse 7&lt;br&gt;<br /> ''Eglible participants:''BfA MKG, MfA MKG, VK, Freie Kunst, Media Architecture&lt;br&gt;<br /> ''First meeting:''Tuesday, 11th of April, 11:00-12:30 + 13:30-15:00&lt;br&gt;<br /> <br /> == Organisms ==<br /> We collect information about different organisms here:<br /> [[GMU:Lebendige_Spiele:Organisms|Organisms]]<br /> <br /> ==Course content==<br /> Living things occur in many games -but usually, they are either simulated, represented by dead matter or other human players.<br /> <br /> In this course, we will explore how living things can play a role in playful interactions.<br /> Students will develop a concept for an experimental game, set it up as a team and present in at an exhibition of a game conference in Düsseldorf.<br /> Practical skills such as microbiological lab-practice, electronics, image analysis, computer graphics and simple mechanics will be taught as needed.<br /> <br /> ===German Version===<br /> Das Lebendige kommt in vielen Spielen vor - seine Rolle wird jedoch meist mit toter Materie, Algorithmen oder menschlichen Mitspielern besetzt.<br /> <br /> Im Kurs wird ausgelotet, wie das Lebendige in Spiele mit einbezogen werden kann.<br /> Ein von den Studierenden erarbeiteter experimenteller Spielentwurf wird im Anschluss praktisch in der Gruppe umgesetzt und im Rahmen einer Ausstellung auf einer Konferenz präsentiert.<br /> Dazu werden je nach Bedarf und Interesse Techniken aus den Bereichen Mikrobiologie, Elektronik, Bildverarbeitung, Computergrafik und Mechanik vermittelt.</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:The_Hidden_Layer:_Artificial_Intelligence_in_creative_contexts&diff=90604 2017-04-11T13:46:18Z

<p>Fbonowski: </p> <hr /> <div>=The Hidden Layer=<br /> Artificial Intelligence in creative contexts.<br /> <br /> ==Formalities==<br /> ''Lecturer:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br&gt;<br /> ''Credits:'' 6 [[ECTS]], 4 [[SWS]]&lt;br&gt;<br /> ''Date:''Wednesday 9:15-12:30&lt;br&gt;<br /> ''Venue:'' Raum 204, Marienstrasse 7&lt;br&gt;<br /> ''Eglible participants:'' BfA MKG, MfA MKG, VK, Media Architecture, PD, Diplom Kunst&lt;br&gt;<br /> ''First meeting:'' Wednesday, 12th of April 9:15-12:30&lt;br&gt;<br /> <br /> ==Application==<br /> We participate in the '''Zentrale Projektvergabe der Fakultät Kunst und Gestaltung.'''&lt;br&gt;<br /> So please... '''Come to the &quot;Projektbörse&quot; on Monday, 3. April 11:00-12.30 in Audimax'''<br /> <br /> Preference will be given to those who &quot;win&quot; a place there, everybody else is welcome if there is still capacity.<br /> <br /> <br /> ==Course content==<br /> ''How does the world look like if you happen to be an artificial intelligence?''<br /> <br /> ''What's going on when machines cathegorize sensual information?''&lt;br /&gt;<br /> ''What's their inner model of the world?''&lt;br /&gt;<br /> ''How do they make decisions?''&lt;br /&gt;<br /> ''How can they express themselves?''&lt;br /&gt;<br /> <br /> ''Are their intentions benign?''<br /> <br /> <br /> During the course, we will collect our own data and use classical machine learning algorithms to develop an understanding for a datadriven perspective on the world.<br /> <br /> The focus will be put on cathegorizing and generating images, texts and sound.<br /> <br /> As part of your exercises you will conduct measurements, do research and apply algorithms that were presented during the course.<br /> <br /> Programming experience is welcome - if you don't have any, but you bring a lot of interest for the topic, you can form a team with other participants with more technical know how.</div>

Fbonowski https://www.uni-weimar.de/kunst-und-gestaltung/wiki/index.php?title=GMU:Lebendige_Spiele&diff=90603 2017-04-11T13:46:00Z

<p>Fbonowski: </p> <hr /> <div>=Spiele mit dem Lebendigen / Lebendige Spiele =<br /> Artificial Intelligence in creative contexts.<br /> Biogames: Playful interactions with the Living<br /> ==Formalities==<br /> ''Lecturer:'' [[GMU:Felix Bonowski|Felix Bonowski]]&lt;br&gt;<br /> ''Credits:'' 6 [[ECTS]], 4 [[SWS]]&lt;br&gt;<br /> ''Date:''Tuesday, 11:00-12:30 + 13:30-15:00&lt;br&gt;<br /> ''Venue:'' DIY Biolab + Raum 201, 204, Marienstrasse 7&lt;br&gt;<br /> ''Eglible participants:''BfA MKG, MfA MKG, VK, Freie Kunst, Media Architecture&lt;br&gt;<br /> ''First meeting:''Tuesday, 11th of April, 11:00-12:30 + 13:30-15:00&lt;br&gt;<br /> <br /> ==Application==<br /> We participate in the '''Zentrale Projektvergabe der Fakultät Kunst und Gestaltung.'''&lt;br&gt;<br /> So please... '''Come to the &quot;Projektbörse&quot; on Monday, 3. April 11:00-12.30 in Audimax'''<br /> <br /> Preference will be given to those who &quot;win&quot; a place there, everybody else is welcome if there is still capacity.<br /> <br /> <br /> ==Course content==<br /> Living things occur in many games -but usually, they are either simulated, represented by dead matter or other human players.<br /> <br /> In this course, we will explore how living things can play a role in playful interactions.<br /> Students will develop a concept for an experimental game, set it up as a team and present in at an exhibition of a game conference in Düsseldorf.<br /> Practical skills such as microbiological lab-practice, electronics, image analysis, computer graphics and simple mechanics will be taught as needed.<br /> <br /> ===German Version===<br /> Das Lebendige kommt in vielen Spielen vor - seine Rolle wird jedoch meist mit toter Materie, Algorithmen oder menschlichen Mitspielern besetzt.<br /> <br /> Im Kurs wird ausgelotet, wie das Lebendige in Spiele mit einbezogen werden kann.<br /> Ein von den Studierenden erarbeiteter experimenteller Spielentwurf wird im Anschluss praktisch in der Gruppe umgesetzt und im Rahmen einer Ausstellung auf einer Konferenz präsentiert.<br /> Dazu werden je nach Bedarf und Interesse Techniken aus den Bereichen Mikrobiologie, Elektronik, Bildverarbeitung, Computergrafik und Mechanik vermittelt.</div>

Fbonowski