Readings and Resources

As stated in my bio, I love learning. I’ve added some of my favourite resources below. Of course, I can only add things I’ve read at least a couple of chapters of. If you disagree with some of my resources or have any suggestions, feel free to contact me.

Math

Analysis

Understanding Analysis by Steven Abbott
Real Analysis by Royden and Fitzpatrick
Real Analysis by Folland

Linear Algebra

Linear Algebra Done Right by Sheldon Axler
Linear Algebra and it’s Applications by Gilbert Strang

Probability Theory

*Knowing the Odds: An Introduction to Probability by John B. Walsh
Probability: Theory and Examples by Rick Durrettc
Probability and Stochastics by Erhan Cinlar

Other

Complex Variables by Steven D. Fisher
A Walk Through Combinatorics by Miklos Bona

Statistics

Statistical Inference by Berger and Casella
Bayesian Forecasting and Dynamic Models by Mike West and Jeff Harrison
An Introduction to Statistical Learning with Applications in R
Probabilistic Machine Learning: An Introduction by Kevin Patrick Murphy

Programming

R for Data Science by Hadley Wickham and Garrett Grolemund
Python Data Science Handbook
Introduction to Computation and Programming Using Python by John V. Guttag