Useful links

Some interesting links regarding machine learning, deep learning and AI in general.

Courses

• Deep Learning Course by François Fleuret, taught at EPFL and then University of Geneva, containing lecture videos, slides and practical materials: https://fleuret.org/dlc/

• MIT 6.S191 “Introduction to Deep Learning” course, video playlist

• Deep Learning Course by Vincent Barra, Professor at Clermont-Auvergne: https://vbarra.github.io/DLbook/intro.html

Books

• Goodfellow, I., Bengio, Y., Courville, A., 2016. Deep learning. MIT Press. link (html)

• Fleuret F., 2024. The Little Book of Deep Learning. link (pdf)

• Zhang, Aston and Lipton, Zachary C. and Li, Mu and Smola, Alexander J., 2023. Dive into Deep Learning. Cambridge University Press. link (html) with notebooks in PyTorch/MXNet/JaX/TensorFlow

• Chloé-Agathe Azencott, 2022. Introduction au Machine Learning. Dunod InfoSup. link (pdf)

• Aggarwal C. C., 2023. Neural Networks and Deep Learning, A Textbook. Springer

Articles

• Mehta, P., Bukov, M., Wang, C.-H., Day, A.G.R., Richardson, C., Fisher, C.K., Schwab, D.J., 2019. A high-bias, low-variance introduction to Machine Learning for physicists. Physics Reports 810, 1–124. https://doi.org/10.1016/j.physrep.2019.03.001, arXiv:1803.08823, notebooks