Teaching

Datascience @ ENS 2022

1. Exercises
2. Notebook about stochastic gradient descent
3. Intro to pytorch — Simple neural network — ConvNet

Optimization for datascience, 2022

Good reference with prerequisites : https://mml-book.github.io/ (main focus on chapter 5, lots of important things in chapters 2, 3, 4)

Reference for the course : https://web.stanford.edu/~boyd/cvxbook/

1. Introduction / algebra reminders / calculus reminders / exercices
2. Gradient descent
3. Proximal Gradient descent
4. Stochastic Gradient descent
5. Variance reduction methods and Exercises about implicit bias

Machine learning and python, 2020

1. Python introduction and Machine learning successes
2. Introduction to machine learning
3. Linear regression and Scikit-learn
4. Neural networks