Math Material

All the material shared in this section is not mine and is shared by the mentioned authors in their webpages. The only objective of this page is to provide useful and free-access material for a complete and deep understanding of Math. I'm probably not aware of many good lecture notes/courses, so feel free to send me additional references to add!

Linear Algebra

• Online course held by W. Gilbert Strang (MIT) for advanced undergraduates and graduate students

• A more advanced course by Terence Tao

• 3blue1brown animated short lectures that give a deep understanding of the essentials of Linear Algebra (and many other topics)

Real Analysis and Measure Theory

• Online course held by Claudio Landim (IMPA) for advanced undergraduates and graduate students 

• Books by Efe A. Ok (NYU), with more advanced material on Measure Theory. At the same link you can find also material for applied point-set topology and order theory

• Lecture Notes by Gabriel Khan (ISU)  based on Royden-Fitzpatrick's textbook and the lecture notes by Timothy McNichol

• Book "Introduction to Real Analysis, Volume I" and "Volume II" by Jiří Lebl

• More advanced courses on Analysis I and Analysis II and Measure Theory by Terence Tao

• Asymptotic Theory notes, more oriented to statistic by David R. Hunter (UPenn)

Courses for Econ graduate PhD students

• Piotr Zwiernik's Lecture notes, which cover an introductory course in Real Analysis, Linear Algebra, Measure Theory, Fixed Point theorems and Correspondences

• Various Courses from the department of Mathematics (Oxford)

• Course on Differential Equations and Linear Algebra by Gilbert Strang (MIT)

• Youtube course by Rajiv Sethi

Miscellaneous

• Elements of information Theory by Thomas M. Cover and Joy A. Thomas

• Convex Optimization by S. Boyd and L. Vandenberghe

• The Elements of statistical learning by T. Hastie, R. Tibshirani and J. Friedman

• Foundations of Machine Learning by M. Mohri, A. Rostamizadeh and A. Talwalkar