Machine Learning

Introduction to Machine Learning

General Information

Lecturer: Prof. Dr. Benno Stein
Lab advisors: Janek Bevendorff, Johannes Kiesel, Nailia Mirzakhmedova
Workload: 2 SWS Lecture, 1 SWS Lab
ECTS Credits: 4.5 or 6 depending on degree programme
Lecture: Th. 9:15am - 10:45am (weekly starting October 20th). Marienstraße 13 C - Hörsaal A
Lab: Th. 11:00am - 12:30pm (biweekly starting October 27th). Marienstraße 13 C - Hörsaal A
Examination: Tu. Feb 21st, 8:00am - 10:00am, Marienstraße 13 C - Hörsaal A + B


Lab Class

Active participation in the lab class is a requirement for admission to the final exam.

To submit your solutions to the lab class exercises, you must enrol in the Moodle course for the lecture.  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.

  • 27.10.2022 Lab Class 1
    Lab class introduction
    Group selection open [moodle]

  • 09.11.2022 23:59: submission deadline for exercise sheet 1 annotations [moodle]

  • 10.11.2022 Lab Class 2
    Lab class machine learning basics 1
    Discussion of exercise sheet 1: [worksheet]

  • 24.11.2022 Lab Class 3
    Lab class machine learning basics 2
    Discussion of exercise sheet 2: [worksheet]

  • 08.12.2022 Lab Class 4
    Lab class linear models
    Discussion of exercise sheet 3: [worksheet]

  • 12.01.2023 Lab Class 5
    Lab class neural networks
    Discussion of exercise sheet 4: [worksheet]

  • 26.01.2023 Lab Class 6
    Lab class decision trees
    Discussion of exercise sheet 5: [worksheet]

  • 02.02.2023 Lab Class 7
    Lab class bayesian learning + Q&A (both lecture and lab class time slot)
    Discussion of exercise sheet 6: [worksheet]




Please find the literature in the lecture slides.