11 Best Data Science Books
Goal: Find the best Data Science books according to the internet (not just one person's opinion).
Method:
- Search for "best data science books" and study the top 5+ pages.
- Add only the books mentioned 2+ times.
- Rank the results neatly here.
11 Best Data Science Books
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Practical Statistics for Data Scientists
50+ Essential Concepts Using R and Python
by Peter Bruce
Introduction to Machine Learning with Python
A Guide for Data Scientists
by Andreas C. Müller
Introduction to Probability
by Joseph K. Blitzstein
Python Data Science Handbook
Essential Tools for Working with Data
by Jake VanderPlas
Python for Data Analysis
Data Wrangling with Pandas, NumPy, and IPython
by Wes McKinney
R for Data Science
Import, Tidy, Transform, Visualize, and Model Data
by Hadley Wickham
Data Science from Scratch
First Principles with Python
by Joel Grus
Head First Statistics
A Brain-Friendly Guide
by Dawn Griffiths
Pattern Recognition and Machine Learning
by Christopher M. Bishop
The Art of Statistics
How to Learn from Data
by David Spiegelhalter
Sources
- 1
12 Best Data Science Books in 2023 | Beginner to Pro
hackr.io
- 2
Best Data Science Books — Free and Paid — Editorial Recommendations for 2022 | Towards AI
pub.towardsai.net
- 3
Data Science Books | Top Data Science Books To Transform
analyticsvidhya.com
- 4
Top 25 Data Science Books in 2023
mygreatlearning.com
- 5
Best Data Science Books for Beginners
simplilearn.com
Edited by
Software engineer whose passion for tracking book recommendations from podcasts inspired the creation of MRB.
Lead investor at 3one4 Capital whose startup expertise and love for books helped shaped MRB and its growth.
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