Machine Learning

Introduction to Machine Learning

General Information

Lecturer: Prof. Dr. Benno Stein
Lab advisors: Michael Völske
Student tutors: Le Anh Phuong
Workload: 2 SWS Lecture, 1 SWS Lab
ECTS Credits: 4.5 for CS4DM, CSM, MI, and HCI before 2019; 6 for DE and HCI since 2019
Lecture: Th. 9:15am - 10:45am (weekly starting October 24th). Marienstraße 13 C - Hörsaal C
Lab: Th. 11:00am - 12:30pm (biweekly starting October 24th). Marienstraße 13 C - Hörsaal C
Examination: Friday, February 14th, 2020, 10:00am


Lab Class

Active participation in the lab class is a requirement for admission to the final exam. Depending on the number of ECTS credits you receive for the course, there is a different minimum score you must attain in the exercises. Details are printed at the top of each exercise sheet.

To submit your solutions to the lab class exercises, you must enrol in the Moodle course for the lecture. The required enrolment key will be announced in the first lab class.

Working in groups of up to 3 students is encouraged -- once you have formed a group, each member must select the same group number in Moodle. The deadline and the exercises to be submitted are printed on each exercise sheet. Note also the instructions printed at the top of the exercise sheet, and pay special attention to which exercises you must submit.

  • 24.10.2019
    Lab class introduction; Exercise 1: Learning Problems, Regression [worksheet]
    Moodle introduction [slides]
    Group selection open [moodle]

  • 31.10.2019: no lecture (public holiday)

  • 07.11.2019
    Python basics [notebooks] (external link)
    Standard library, numpy, matplotlib [notebook] [slides]

  • 11.11.2019 11:00 am: submission deadline for exercise 1 [moodle]

  • 14.11.2019
    Exercise 2: Concept Learning [worksheet] [additional test cases]

  • 21.11.2019
    Discussion of Exercise 1
    Tutorial: pandas, LMS, plotting [notebook] [slides]

  • 25.11.2019 11:00 am: submission deadline for exercise 2 [moodle]
    Last chance to change group selection [moodle]

  • 28.11.2019
    Discussion of exercise 2
    Exercise 3: Decision Trees [worksheet]
    Conditional entropy [slides] [notebook]

  • 09.12.2019 11:00 am: submission deadline for exercise 3 [moodle]

  • 12.12.2019
    Discussion of exercise 3
    Exercise 4: Statistical Learning [worksheet] [starter-code]

  • 06.01.2020 11:00 am: submission deadline for exercise 4

  • 09.01.2020
    Discussion of exercise 4
    Exercise 5: Neural Networks [worksheet]

  • 22.01.2020 23:59 pm: submission deadline for exercise 5 [moodle]

  • 23.01.2020
    Discussion of exercise 5
    Exercise 6: Cluster Analysis [worksheet]

  • 03.02.2020
    Bonus exercise [worksheet]

  • 05.02.2020 23:59 pm: submission deadline for exercise 6 [moodle]

  • 06.02.2020
    Discussion of exercise 6
    Exam preparation

  • 09.02.2020 23:59 pm: submission deadline for bonus exercise [moodle]

  • 12.02.2020 13:30 pm
    Extra lab class appointment in Marienstr. 13, lecture hall C
    Exam preparation II


Please find the literature in the script.