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11 Best Data Science Books

Goal: Find the best Data Science books according to the internet (not just one person's opinion).

Method:

  1. Search for "best data science books" and study the top 5+ pages.
  2. Add only the books mentioned 2+ times.
  3. Rank the results neatly here.

11 Best Data Science Books

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1

Practical Statistics for Data Scientists

50+ Essential Concepts Using R and Python

by Peter Bruce

2

Introduction to Machine Learning with Python

A Guide for Data Scientists

by Andreas C. Müller

3

Introduction to Probability

by Joseph K. Blitzstein

4

Python Data Science Handbook

Essential Tools for Working with Data

by Jake VanderPlas

5

Python for Data Analysis

Data Wrangling with Pandas, NumPy, and IPython

by Wes McKinney

6

R for Data Science

Import, Tidy, Transform, Visualize, and Model Data

by Hadley Wickham

7

Naked Statistics

Stripping the Dread from the Data

by Charles Wheelan

Also recommended by:

Keith Rabois

8

Data Science from Scratch

First Principles with Python

by Joel Grus

9

Head First Statistics

A Brain-Friendly Guide

by Dawn Griffiths

10

Pattern Recognition and Machine Learning

by Christopher M. Bishop

11

The Art of Statistics

How to Learn from Data

by David Spiegelhalter

Sources

Edited by

Richard Reis

Software engineer whose passion for tracking book recommendations from podcasts inspired the creation of MRB.

Anurag Ramdasan

Lead investor at 3one4 Capital whose startup expertise and love for books helped shaped MRB and its growth.

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