Machine Learning 2
General Information
 Machine Learning 2 is a 9 LP (9 ECTS) credits module.
 Machine Learning 2X is a 12 LP (12 ECTS) credits module.
Lectures period 
19.04.2022  23.07.2022 
Q&As 
Tuesdays, 14:15  16:00 (online) 
Exercises 
Wednesdays, 10:15  12:00 (Room: A 151) 
Lecture 
Thursdays, 14:15  16:00 (Room: H 104) 
Trainers 
KlausRobert Müller 
Grégoire Montavon 

Contact 

ISIS 

Language 
English 
Frequently asked questions (FAQ):
How to register for the course? There is no preregistration. Just come to the first lecture.
What are the prerequisites? There are now formal prerequisite, however, desirable prerequisites are knowledge in linear algebra and calculus, basic knowledge in probability theory, basic programming knowledge, programming in Python, and Machine Learning 1 or equivalent.
Is it possible to take this course without having taken Machine Learning 1? Yes, ML1 is not a formal prerequisite. However, some methods learned in ML1 (e.g. kernels/SVM, neural networks, PCA, probability models) will be assumed to be known, and extra work might therefore be needed during the first few weeks.
I am from a different university, can I take this course? If you are not a student at TU and want to earn credit, you have to solicit ''Nebenhörerschaft''.
Topics
 LowDimensional Embeddings (LLE, TSNE)
 Component Analyses (CCA, ICA)
 Kernel Learning (structured input, structured outputs, anomaly detection)
 Hidden Markov Models
 Deep Learning (structured input, structured outputs, anomaly detection)
 Bioinformatics
 Explainable AI
List of elective courses
As part of Machine Learning 2X, you need to take one of the following courses:
Note that these courses cannot be taken as standalone courses.