Introduction: Learning & AI

Additional References

The Artificial Intelligence and Machine Learning research group at Princeton University. See also Sanjeev Arora's ICM 2018 plenary lecture on The mathematics of machine learning and deep learning.
Both April and July 2024 issues of the Bulletin of the American Mathematical Society contain a collection of papers on Math and AI.
Besides, the Notices of the AMS have published more pedagogical papers on the mathematical foundations of Machine Learning:
- Machine Learning and Invariant Theory (2023), vol 70, 1205-13,
- Mathematizing Human Perception (2023), vol 70, 1081-88,
- Mathematical Foundations of Graph-Based Bayesian Semi-Supervised Learning (2022), vol 69, 1717-29,
- Model Selection for Optimal Prediction in Statistical Machine Learning (2020), vol 67, 155-168,
- Machine Learning: Mathematical Theory and Scientific Applications (2019), vol 66, 1813-20,
- From Decoupling and Self-Normalization to Machine Learning (2019), vol 66, 1641-46,
The Spring 2020 & 2021 lectures on deep learning by Yann LeCun at the NYU Center for Data Science.
The lectures on data science by Stéphane Mallat at the Collège de France.