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Data Science Books
Showing 1-50 of 5,296
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (Paperback)
by (shelved 250 times as data-science)
avg rating 4.12 — 2,685 ratings — published 2013
Storytelling with Data: A Data Visualization Guide for Business Professionals (Paperback)
by (shelved 226 times as data-science)
avg rating 4.38 — 8,551 ratings — published 2015
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
by (shelved 201 times as data-science)
avg rating 4.59 — 2,362 ratings — published 2013
Python for Data Analysis (Paperback)
by (shelved 198 times as data-science)
avg rating 4.17 — 2,480 ratings — published 2011
The Signal and the Noise: Why So Many Predictions Fail—But Some Don't (Hardcover)
by (shelved 187 times as data-science)
avg rating 3.97 — 53,117 ratings — published 2012
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (Hardcover)
by (shelved 185 times as data-science)
avg rating 3.87 — 31,017 ratings — published 2016
Data Science from Scratch: First Principles with Python (ebook)
by (shelved 181 times as data-science)
avg rating 3.90 — 1,163 ratings — published 2015
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Hardcover)
by (shelved 181 times as data-science)
avg rating 4.43 — 1,912 ratings — published 2001
Hands-On Machine Learning with Scikit-Learn and TensorFlow (ebook)
by (shelved 174 times as data-science)
avg rating 4.55 — 2,874 ratings — published 2017
Naked Statistics: Stripping the Dread from the Data (Paperback)
by (shelved 174 times as data-science)
avg rating 3.95 — 15,504 ratings — published 2012
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (Kindle Edition)
by (shelved 135 times as data-science)
avg rating 4.53 — 1,247 ratings — published 2016
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are (Hardcover)
by (shelved 135 times as data-science)
avg rating 3.90 — 43,230 ratings — published 2017
Python Data Science Handbook: Essential Tools for Working with Data (Paperback)
by (shelved 135 times as data-science)
avg rating 4.29 — 682 ratings — published 2016
The Art of Statistics: How to Learn from Data (Hardcover)
by (shelved 132 times as data-science)
avg rating 4.15 — 5,975 ratings — published 2019
Practical Statistics for Data Scientists: 50 Essential Concepts (Paperback)
by (shelved 128 times as data-science)
avg rating 4.02 — 553 ratings — published
Data Smart: Using Data Science to Transform Information into Insight (Paperback)
by (shelved 127 times as data-science)
avg rating 4.12 — 1,021 ratings — published 2013
Doing Data Science: Straight Talk from the Frontline (Paperback)
by (shelved 125 times as data-science)
avg rating 3.73 — 568 ratings — published 2013
The Visual Display of Quantitative Information (Hardcover)
by (shelved 114 times as data-science)
avg rating 4.39 — 8,794 ratings — published 1983
Pattern Recognition and Machine Learning (Information Science and Statistics)
by (shelved 100 times as data-science)
avg rating 4.32 — 1,923 ratings — published
Deep Learning (ebook)
by (shelved 97 times as data-science)
avg rating 4.43 — 2,172 ratings — published 2016
Invisible Women: Data Bias in a World Designed for Men (Hardcover)
by (shelved 97 times as data-science)
avg rating 4.33 — 182,388 ratings — published 2019
How to Lie with Statistics (Paperback)
by (shelved 82 times as data-science)
avg rating 3.83 — 18,608 ratings — published 1954
Algorithms to Live By: The Computer Science of Human Decisions (Hardcover)
by (shelved 76 times as data-science)
avg rating 4.12 — 36,050 ratings — published 2016
Designing Data-Intensive Applications (ebook)
by (shelved 75 times as data-science)
avg rating 4.69 — 11,262 ratings — published 2015
Introduction to Machine Learning with Python: A Guide for Data Scientists (Paperback)
by (shelved 74 times as data-science)
avg rating 4.33 — 603 ratings — published 2015
Deep Learning with Python (Paperback)
by (shelved 73 times as data-science)
avg rating 4.57 — 1,437 ratings — published 2017
The Hundred-Page Machine Learning Book (Paperback)
by (shelved 71 times as data-science)
avg rating 4.25 — 1,493 ratings — published
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python (Paperback)
by (shelved 68 times as data-science)
avg rating 4.22 — 267 ratings — published
Superforecasting: The Art and Science of Prediction (Hardcover)
by (shelved 68 times as data-science)
avg rating 4.08 — 23,078 ratings — published 2015
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (Paperback)
by (shelved 65 times as data-science)
avg rating 3.66 — 2,129 ratings — published 2013
The Book of Why: The New Science of Cause and Effect (Hardcover)
by (shelved 64 times as data-science)
avg rating 3.93 — 6,822 ratings — published 2018
Big Data: A Revolution That Will Transform How We Live, Work, and Think (Hardcover)
by (shelved 64 times as data-science)
avg rating 3.69 — 8,697 ratings — published 2013
Applied Predictive Modeling (Hardcover)
by (shelved 61 times as data-science)
avg rating 4.40 — 344 ratings — published 2013
How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers (Paperback)
by (shelved 60 times as data-science)
avg rating 4.11 — 8,581 ratings — published 2020
The Art of Data Science: A Guide for Anyone Who Works with Data (ebook)
by (shelved 60 times as data-science)
avg rating 3.70 — 301 ratings — published 2015
Lean Analytics: Use Data to Build a Better Startup Faster (Hardcover)
by (shelved 58 times as data-science)
avg rating 4.10 — 8,256 ratings — published 2013
Think Stats (Paperback)
by (shelved 56 times as data-science)
avg rating 3.65 — 469 ratings — published 2011
Dataclysm: Who We Are (When We Think No One's Looking)
by (shelved 55 times as data-science)
avg rating 3.73 — 12,536 ratings — published 2014
Python Machine Learning (Paperback)
by (shelved 54 times as data-science)
avg rating 4.24 — 758 ratings — published 2015
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (Hardcover)
by (shelved 49 times as data-science)
avg rating 3.73 — 6,555 ratings — published 2015
Machine Learning: A Probabilistic Perspective (Hardcover)
by (shelved 48 times as data-science)
avg rating 4.35 — 524 ratings — published
Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists (Paperback)
by (shelved 45 times as data-science)
avg rating 4.07 — 313 ratings — published 2010
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (Paperback)
by (shelved 43 times as data-science)
avg rating 4.43 — 1,186 ratings — published 2022
Forecasting: principles and practice (Paperback)
by (shelved 43 times as data-science)
avg rating 4.39 — 319 ratings — published 2013
Mathematics for Machine Learning: 1st Edition (Kindle Edition)
by (shelved 41 times as data-science)
avg rating 4.32 — 275 ratings — published
Factfulness: Ten Reasons We're Wrong About the World – and Why Things Are Better Than You Think (Hardcover)
by (shelved 41 times as data-science)
avg rating 4.35 — 206,906 ratings — published 2018
Statistics Done Wrong: The Woefully Complete Guide (Paperback)
by (shelved 41 times as data-science)
avg rating 4.19 — 1,105 ratings — published 2013
Bayesian Data Analysis (Hardcover)
by (shelved 41 times as data-science)
avg rating 4.21 — 544 ratings — published 1995
Numsense! Data Science for the Layman: No Math Added (Kindle Edition)
by (shelved 40 times as data-science)
avg rating 4.14 — 625 ratings — published
Artificial Intelligence: A Modern Approach (Hardcover)
by (shelved 39 times as data-science)
avg rating 4.21 — 4,496 ratings — published 1994
“An issue with current data science methodologies is that the impact of contextual awareness is underestimated since the problem is much more complex. At times we incorrectly equate correlation with causation based on incomplete data or lack of understanding sensitive dependencies between data sets. - Tom Golway”
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“Businesses should free themselves from dogma, especially when leveraging data to build a business. No one got very far living out other people’s thinking.”
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