Teaching

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