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Books and on-line resources

Recommended reading. You can use or own resources which, however, may differ in some terminology.

[Russell-Norvig2010] is the main course book. We will not need the whole book. A more detailed recommendation will be provided throughout the course. Note the large on-line content at http://aima.cs.berkeley.edu

Especially when discussing Reinforcement learning and MDPs, we will make use of [Sutton-Barto2018], on-line pdf.

[Bishop2006] is an excellent textbook for machine learning, classifiers, ROC, perceptron … PDF is freely downloadable.

For Python we recommend [Wentworth2012] or [Downey2009]; the newer and Python 3.x fully compatible [Wentworth2012] is probably the better option. Object-Oriented Programming in Python is a good on-line textbook.

You can also use multiple on-line resources:

CTU courses for possible specializations. If you fall in love with some parts of our course, you may dig deeper in the following courses:

You may also consider participating in research projects as a summer intern or doing an individual project or accomplishing a bachelor/master thesis.

courses/be5b33kui/literature.txt · Last modified: 2021/03/28 21:39 by hoffmmat