A Mathematical Core for Data Scientists (10 books)

Listopia > A Mathematical Core for Data Scientists

As an engineer who transitioned to becoming a Data Scientist, I needed a lot of self-learning to understand the core principles behind statistical inference and machine learning. The books in this list are no-nonsense, but the prerequisites are minimal (usually just calculus and maybe a sprinkling of linear algebra).

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1	Linear Algebra and Learning from Data by Gilbert Strang 4.35 avg rating — 48 ratings score: 199, and 2 people voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
2	Introduction to Probability by Joseph K. Blitzstein 4.53 avg rating — 181 ratings score: 197, and 2 people voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
3	All of Statistics: A Concise Course in Statistical Inference by Larry Wasserman 4.26 avg rating — 410 ratings score: 99, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
4	Statistical Inference by George Casella 4.17 avg rating — 399 ratings score: 98, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
5	Introduction to Linear Algebra by Gilbert Strang 4.25 avg rating — 710 ratings score: 96, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
6	Calculus by Michael Spivak 4.53 avg rating — 1,019 ratings score: 95, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
7	Pattern Recognition and Machine Learning by Christopher M. Bishop 4.32 avg rating — 1,913 ratings score: 94, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
8	Learning From Data: A Short Course by Yaser S. Abu-Mostafa 4.38 avg rating — 441 ratings score: 93, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
9	The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie 4.43 avg rating — 1,907 ratings score: 92, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars
10	Deep Learning by Ian Goodfellow 4.44 avg rating — 2,154 ratings score: 91, and 1 person voted	Error rating book. Refresh and try again. Rate this book Clear rating 1 of 5 stars 2 of 5 stars 3 of 5 stars 4 of 5 stars 5 of 5 stars