Resources for education in statistics and machine learning: from advanced undergraduate to research level
This repository contains links to references (books, courses, etc) that are useful for learning statistics and machine learning (as well as some neighboring topics). References for background materials such as linear algebra, calculus/analysis/measure theory, probability theory, etc, are usually not included.
The level of the references starts from advanced undergraduate stats/math/CS and in some cases goes up to the research level. The books are often standard references and textbooks, used at leading institutions. In particular, several of the books are used in the standard curriculum of the PhD program in Statistics at Stanford University (where I learned from them as well), as well as at the University of Pennsylvania (where I work). The goal is to benefit students, researchers seeking to enter new areas, and lifelong learners.
For each topic, materials are listed in a rough order of from basic to advanced.
The list is highly subjective and incomplete, reflecting my own preferences, interests and biases. For instance, there is an emphasis on theoretical material. Most of the references included here are something that I have at least partially (and sometimes extensively) studied; and found helpful. Others are on my to-read list. Several topics are omitted due to lack of expertise (e.g., causal inference, Bayesian statistics, time series, sequential decision-making, functional data analysis, biostatistics, ...).
The links are to freely available author copies if those are available, or to online marketplaces otherwise (you are encouraged to search for the best price).
How to use these materials to learn: To be an efficient researcher, certain core material must be mastered. However, there is too much specialized knowledge, and it can be overwhelming to know it all. Fortunately, it is often enough to know what type of results/methods/tools are available, and where to find them. When they are needed, they can be recalled and used.
Please feel free to contact me with suggestions.
This section is the most detailed one, as it is the closest to my research.
This is subject to active development and research. There is no complete reference.