27 books
—
3 voters
Data Science Books
Showing 1-50 of 4,919
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (Paperback)
by (shelved 253 times as data-science)
avg rating 4.13 — 2,648 ratings — published 2013
Storytelling with Data: A Data Visualization Guide for Business Professionals (Paperback)
by (shelved 218 times as data-science)
avg rating 4.39 — 8,176 ratings — published 2015
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
by (shelved 202 times as data-science)
avg rating 4.59 — 2,337 ratings — published 2013
Python for Data Analysis (Paperback)
by (shelved 195 times as data-science)
avg rating 4.17 — 2,452 ratings — published 2011
The Signal and the Noise: Why So Many Predictions Fail—But Some Don't (Hardcover)
by (shelved 189 times as data-science)
avg rating 3.97 — 52,464 ratings — published 2012
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (Hardcover)
by (shelved 187 times as data-science)
avg rating 3.87 — 30,127 ratings — published 2016
Data Science from Scratch: First Principles with Python (ebook)
by (shelved 182 times as data-science)
avg rating 3.91 — 1,151 ratings — published 2015
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Hardcover)
by (shelved 179 times as data-science)
avg rating 4.43 — 1,888 ratings — published 2001
Naked Statistics: Stripping the Dread from the Data (Paperback)
by (shelved 177 times as data-science)
avg rating 3.96 — 15,195 ratings — published 2012
Hands-On Machine Learning with Scikit-Learn and TensorFlow (ebook)
by (shelved 173 times as data-science)
avg rating 4.55 — 2,808 ratings — published 2017
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 3.91 — 42,657 ratings — published 2017
Python Data Science Handbook: Essential Tools for Working with Data (Paperback)
by (shelved 135 times as data-science)
avg rating 4.30 — 674 ratings — published 2016
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (Kindle Edition)
by (shelved 131 times as data-science)
avg rating 4.53 — 1,228 ratings — published 2016
The Art of Statistics: How to Learn from Data (Hardcover)
by (shelved 129 times as data-science)
avg rating 4.15 — 5,697 ratings — published 2019
Practical Statistics for Data Scientists: 50 Essential Concepts (Paperback)
by (shelved 128 times as data-science)
avg rating 4.02 — 542 ratings — published
Data Smart: Using Data Science to Transform Information into Insight (Paperback)
by (shelved 126 times as data-science)
avg rating 4.12 — 1,019 ratings — published 2013
Doing Data Science: Straight Talk from the Frontline (Paperback)
by (shelved 125 times as data-science)
avg rating 3.74 — 567 ratings — published 2013
The Visual Display of Quantitative Information (Hardcover)
by (shelved 113 times as data-science)
avg rating 4.39 — 8,676 ratings — published 1983
Pattern Recognition and Machine Learning (Information Science and Statistics)
by (shelved 101 times as data-science)
avg rating 4.32 — 1,903 ratings — published
Deep Learning (ebook)
by (shelved 99 times as data-science)
avg rating 4.44 — 2,124 ratings — published 2016
Invisible Women: Data Bias in a World Designed for Men (Hardcover)
by (shelved 94 times as data-science)
avg rating 4.34 — 169,440 ratings — published 2019
How to Lie with Statistics (Paperback)
by (shelved 80 times as data-science)
avg rating 3.84 — 18,072 ratings — published 1954
Algorithms to Live By: The Computer Science of Human Decisions (Hardcover)
by (shelved 77 times as data-science)
avg rating 4.12 — 35,074 ratings — published 2016
Introduction to Machine Learning with Python: A Guide for Data Scientists (Paperback)
by (shelved 75 times as data-science)
avg rating 4.33 — 596 ratings — published 2015
Designing Data-Intensive Applications (ebook)
by (shelved 74 times as data-science)
avg rating 4.70 — 10,620 ratings — published 2015
Deep Learning with Python (Paperback)
by (shelved 73 times as data-science)
avg rating 4.57 — 1,399 ratings — published 2017
The Hundred-Page Machine Learning Book (Paperback)
by (shelved 71 times as data-science)
avg rating 4.25 — 1,441 ratings — published
Superforecasting: The Art and Science of Prediction (Hardcover)
by (shelved 70 times as data-science)
avg rating 4.08 — 22,282 ratings — published 2015
Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (Paperback)
by (shelved 66 times as data-science)
avg rating 3.66 — 2,124 ratings — published 2013
Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python (Paperback)
by (shelved 66 times as data-science)
avg rating 4.21 — 259 ratings — published
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 — 8,677 ratings — published 2013
The Book of Why: The New Science of Cause and Effect (Hardcover)
by (shelved 62 times as data-science)
avg rating 3.94 — 6,603 ratings — published 2018
Applied Predictive Modeling (Hardcover)
by (shelved 62 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 58 times as data-science)
avg rating 4.12 — 8,289 ratings — published 2020
The Art of Data Science: A Guide for Anyone Who Works with Data (ebook)
by (shelved 58 times as data-science)
avg rating 3.71 — 298 ratings — published 2015
Lean Analytics: Use Data to Build a Better Startup Faster (Hardcover)
by (shelved 56 times as data-science)
avg rating 4.11 — 8,224 ratings — published 2013
Dataclysm: Who We Are (When We Think No One's Looking)
by (shelved 56 times as data-science)
avg rating 3.73 — 12,482 ratings — published 2014
Think Stats (Paperback)
by (shelved 56 times as data-science)
avg rating 3.64 — 469 ratings — published 2011
Python Machine Learning (Paperback)
by (shelved 53 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 51 times as data-science)
avg rating 3.74 — 6,465 ratings — published 2015
Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists (Paperback)
by (shelved 48 times as data-science)
avg rating 4.07 — 313 ratings — published 2010
Machine Learning: A Probabilistic Perspective (Hardcover)
by (shelved 47 times as data-science)
avg rating 4.34 — 520 ratings — published
Forecasting: principles and practice (Paperback)
by (shelved 42 times as data-science)
avg rating 4.39 — 317 ratings — published 2013
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (Paperback)
by (shelved 41 times as data-science)
avg rating 4.45 — 1,035 ratings — published 2022
Mathematics for Machine Learning: 1st Edition (Kindle Edition)
by (shelved 41 times as data-science)
avg rating 4.31 — 251 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 4.36 — 202,217 ratings — published 2018
Numsense! Data Science for the Layman: No Math Added (Kindle Edition)
by (shelved 41 times as data-science)
avg rating 4.14 — 620 ratings — published
Statistics Done Wrong: The Woefully Complete Guide (Paperback)
by (shelved 41 times as data-science)
avg rating 4.19 — 1,087 ratings — published 2013
Bayesian Data Analysis (Hardcover)
by (shelved 41 times as data-science)
avg rating 4.21 — 539 ratings — published 1995
Artificial Intelligence: A Modern Approach (Hardcover)
by (shelved 40 times as data-science)
avg rating 4.20 — 4,454 ratings — published 1994
“Machine learning modeling and testing on sample data and going through the business user acceptance test can surprise you!
And it will definitely make you to rethink on your feature selection and data sampling methods.”
― Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data : Illustrations with R & Python
And it will definitely make you to rethink on your feature selection and data sampling methods.”
― Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data : Illustrations with R & Python
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