Line 7: Line 7:
  
 
=== Installation + getting started: ===
 
=== Installation + getting started: ===
 +
Included in the ''gensim'' package.
 +
 +
To install, just type
 +
 
<code>pip install gensim</code><br>
 
<code>pip install gensim</code><br>
 +
 +
into a command window.
 +
 
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 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/].
 
Here is a bit of background information an an explanation how to train your own models: [https://rare-technologies.com/word2vec-tutorial/].
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=== Installation + getting started: ===
 
=== Installation + getting started: ===
Included in Gensim. Couldn't test yet due to memory constraints.
+
Included in the ''gensim'' package.
 +
 
 +
To install, just type
 +
 
 +
<code>pip install gensim</code><br>
 +
 
 +
into a command window.
 +
 
 
Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]
 
Documentation is here: [https://radimrehurek.com/gensim/models/wrappers/fasttext.html]
  

Revision as of 11:28, 8 May 2017

General Information on word embeddings

For a general explanation look here: [1]

Word2vec

Made by Google, uses Neural Net, performs good on semantics.

Installation + getting started:

Included in the gensim package.

To install, just type

pip install gensim

into a command window.

Here are some of the things you can do with the model: [2]
Here is a bit of background information an an explanation how to train your own models: [3].

Fastword

Made by Facebook based on word2vec. Better at capturing syntactic relations (like apparent ---> apparently) see here: [4]

Pretrained model files are HUGE - this will be a problem on computers with less than 16GB Memory

Installation + getting started:

Included in the gensim package.

To install, just type

pip install gensim

into a command window.

Documentation is here: [5]

GloVe

Invented by the Natural language processing group in standford. [6]Uses more conventional math instead of Neural Network "Black Magic". Seems to perform very slightly less well than Word2vec and FastWord.

pre trained models