Useful Machine Learning resources

This page is dedicated to all the Machine Learning resources I have used during my studies and that I still use today. Listing them here is a way to pay tribute to all the great person that produced them.

Books

Machine Learning concepts

If you want to learn about statistical Machine Learning concepts like Regression, Classification, Kernel Methods or Neural Networks

• The one I used to read before going to sleep : James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning: with applications in R (Vol. 2). New York: springer.
• The one that almost everyone knows about : Bishop, C. M., & Nasrabadi, N. M. (2006). Pattern recognition and machine learning (Vol. 4, No. 4, p. 738). New York: springer. from Christopher M. Bishop
• Also a great that is good to start Murphy, K. P. (2022). Probabilistic machine learning: an introduction. MIT press. from Kevin Patrick Murphy (Available online for free)

Deep Learning concepts

If you are interrested about concepts like Deep Neural Networks, Markov Chains, Monte Carlo Methods or even Generative Models

• The one that taught me everything about Deep Learning (especially about outdated concepts which are fundamental) : Aggarwal, C. C. (2018). Neural networks and deep learning (Vol. 10, No. 978, p. 3). Cham: springer. from Charu C. Aggarwal

• Murphy, K. P. (2023). Probabilistic machine learning: Advanced topics. MIT press. from Kevin Patrick Murphy (Available online for free)

• The logical next step to the first great book : Bishop, C. M., & Bishop, H. (2024). Deep learning: Foundations and concepts (Vol. 1). Cham, Switzerland: Springer.

• One book that I discovered recently for which I have great interrested : Prince, S. J. (2023). Understanding deep learning. MIT press.

Reinforcement Learning concepts

• One very nice book I used to read : Plaat, A. (2022). Deep reinforcement learning (Vol. 10, pp. 978-981). Singapore: Springer. available on arXiv for free

Neural ODE concepts

• A complete and great ressource if you want to go deeper into NeuralODEs : Kidger, P. (2022). On neural differential equations. arXiv preprint arXiv:2202.02435.

Videos

Online Deep Learning course from CNRS

The CNRS deployed this great resource that I recommend to dive into if you want to start in Deep Learning but you don’t know how : Fiddle Deep Learning