Python Programming for Machine Learning

Python Programming for Machine Learning is an optional course in the module "Machine Learning - Theory and Applications" and is worth 3 LP (3 ECTS credits).

In the general case, it is not possible to take the Python course as a standalone course. There are possible exceptions to this (e.g. it complements another ML or related course you are taking in parallel). In that case, a special request needs to be made.

The course will be split in two tracks A and B, with the same content, but held at different times of the week/day. Students can opt for either of these.

Track A is recommended for ML2 ("Maschinelles Lernen - Theorie und Anwendung") students as it has no time conflict with that course.

• Course Period:	TBA
  Lectures:	TBA [Track A]
  	TBA [Track B]
  Exercises:	TBA [Track B]
  	TBA [Track A]
  	TBA
  Exam:	TBA
  Language:	English
  Trainers	Sergej Dogadov
  	Philipp Seegerer
  Contact	sergej.dogadov@campus.tu-berlin.de
  ISIS:	TBA

Frequently Asked Questions (FAQ)

• When does the course start? TBA

• How to register for the course? Pre-registration is not needed.

Main Topics

• Python Basics
• Numpy / Performance / Plotting
• Rounding / Overflow / Linear Algebra
• Randomness / Simulation

Additional Topics

• Linear Models (Regression, PCA)
• Low-Level Extensions (F2PY)

Knowledge of elementary programming concepts will be helpful. Be aware that lack of such knowledge will increase the time demand of the class. In that case, you should consider to prepare with a python beginner class.

Homework is submitted via the ISIS page.

students from other universities

If you are not a student at TU and want to earn credit, you have to solicit ''Nebenhörerschaft'':

• print out the forms concerning Nebenhörerschaft you find on that page
• pass by at my office (see above) to have them signed
• in addition, the dean of faculty IV has to sign
• register at the the Campus Center. You will receive a TUBIT account (see below).