Notes from the Machine Learning course held by Professor Alessio Micheli at University of Pisa 2019-2020 written by Alessandro Cudazzo and Giulia Volpi.
These notes are intended only as support for the study of the subject and as slides side notes. They do not cover the whole program but only a part, to compensate for the missing parts, we recommend the use of slides and books provided by Prof. Micheli. We hope these notes will help future students and if you find any mistakes or want to help extend these notes, feel free to do so with a Pull Request.
What you will find here: Introduction to ML, Linear Model and K-NN, Neural Networks, Validation, Statistical Learning Theory (STL).
What's missing: Concept Learning, SVM, Bias Variance, Deep Learning (CNN, Deep, Rand), SOM, Bayes Learning, RNN, SDL.
# Clone Notes
git clone https://github.com/alessandrocuda/Notes-Machine-Learning-19-20.git
cd Notes-Machine-Learning-19-20
# Compile Notes
make
# Clean
make clean- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request :D
or write an email to: