The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics) 2nd Edition

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For those who love science and mathematics, then this is the book for your reading from Amazon. Some of the chapters include Bootstrap versus Maximum Likelihood, Trees with Simulated Data, Model Averaging and Stacking, etc. It may sound alien to most of us but for the learned, this makes an interesting read, especially for those who are doing their masters or PhDs.

The Elements of statistical learning is more for actuarial science students who will later work in the insurance industry, calculating complex data and refunds to the policy holders.

Some Reviews include the below:

Very comprehensive, sufficiently technical to get most of the plumbing behind machine learning. Very useful as a reference book (actually, there is no other complete reference book).

The authors are the real thing (Tibshirani is the one behind the LASSO regularization technique).

Uses some mathematical statistics without the burdens of measure theory and avoids the obvious but complicated proofs.

I own two copies of this edition, one for the office, one for my house, and the authors generously provide the PDF for travelers like me.

The author’s biography includes those from Wikipedia:

Biography

Robert Tibshirani (born July 10, 1956) is a Professor in the Departments of Statistics and Health Research and Policy at Stanford University. He was a Professor at the University of Toronto from 1985 to 1998. In his work, he develops statistical tools for the analysis of complex datasets, most recently in genomics and proteomics.

His most well-known contributions are the LASSO method, which proposed the use of L1 penalization in regression and related problems, and Significance Analysis of Microarrays. He has also co-authored three well-known books: “Generalized Additive Models”, “An Introduction to the Bootstrap”, and “The Elements of Statistical Learning”, the last of which is available for free from the author’s website.

You can also buy the book by clicking on the image above.