Here I will put all the material I use for teaching. For now, it is just a list of useful links!
Technical tools
- Guide to how to develop on remote hosts
- Very easy introduction to git
- A fully interactive tutorial about git
- When git is a mess
- If you need a review of any technology, check this
Machine Learning
- A good university course on Machine Learning
- A good university course on Probabilistic Graphical Models (including Bayesian Networks, Markov Random Fields, and Conditional Random Fields)
Neural Networks
- The deep learning book . A must.
- An awesome explanation of backpropagation
- A tool to visualize how nn learn (check input and output)
- Another tool to study how and what nn are learning
- Resources to understand convolutions and transposed convolutions: vdumoulin , ezyang
- A nice paper to understand LSTM networks
- Understanding update algorithms Attention and transformers explained visually