This is a collection of notes I've been making for the course Machine Intelligence 1: Supervised Learning at the TU Berlin. Machine Intelligence 1 is the first part of two consecutive courses on topics in machine learning and artificial neural networks taught by Prof. Klaus Obermayer of the Neural Information Processing Group at TU Berlin.
Topics covered throughout the course:
- Artificial neural networks
- Learning and generalization
- Deep Learning and Recurrent architectures
- Elements of statistical learning theory
- Kernel Methods
- Bayesian networks
- Reinforcement learning
See Releases to download the latest pdf files.
Ubuntu:
apt install texlive-fonts-recommended texlive-latex-extra texlive-fonts-extra dvipng texlive-latex-recommended texlive-science texlive-lang-german
Additional packages for Ubuntu releases 14.04:
apt install latex-beamer
Any contribution to add content, visualization and increase the quality of the notes is much appreciated.
Post Issues to report mistakes (e.g. mistakes in the writing, layout mistakes, problems with referencing)
Making Pull requests that fix any issues is very much encouraged and appreciated. Feel free to make a pull request that resolves an issue with the content and eliminates any mistakes. Any advice on writing better Latex is welcome as well. Please keep the scope of changes small to make it easier to spot the differences and identify the contribution in order to speed up the review process and get your changes merges as fast as possible.
For broader changes, open an issue for the proposed broad change so we can discuss it.
At this point I would like to avoid making any major changes to styling but open to discussing them.
Many thanks to Dr. Moritz Augustin, my predecessor in TA'ing this course, for outlining the content of the tutorials and providing me with his own notes.