Data Science Books

Showing 1-50 of 5,033
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking 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 4.13 — 2,671 ratings — published 2013
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Storytelling with Data: A Data Visualization Guide for Business Professionals Storytelling with Data: A Data Visualization Guide for Business Professionals (Paperback)
by (shelved 224 times as data-science)
avg rating 4.38 — 8,370 ratings — published 2015
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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
by (shelved 202 times as data-science)
avg rating 4.59 — 2,355 ratings — published 2013
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Python for Data Analysis Python for Data Analysis (Paperback)
by (shelved 198 times as data-science)
avg rating 4.17 — 2,464 ratings — published 2011
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The Signal and the Noise: Why So Many Predictions Fail—But Some Don't The Signal and the Noise: Why So Many Predictions Fail—But Some Don't (Hardcover)
by (shelved 188 times as data-science)
avg rating 3.97 — 52,727 ratings — published 2012
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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (Hardcover)
by (shelved 188 times as data-science)
avg rating 3.87 — 30,508 ratings — published 2016
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Data Science from Scratch: First Principles with Python Data Science from Scratch: First Principles with Python (ebook)
by (shelved 181 times as data-science)
avg rating 3.90 — 1,158 ratings — published 2015
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Hardcover)
by (shelved 179 times as data-science)
avg rating 4.43 — 1,904 ratings — published 2001
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Naked Statistics: Stripping the Dread from the Data Naked Statistics: Stripping the Dread from the Data (Paperback)
by (shelved 176 times as data-science)
avg rating 3.95 — 15,316 ratings — published 2012
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Hands-On Machine Learning with Scikit-Learn and TensorFlow Hands-On Machine Learning with Scikit-Learn and TensorFlow (ebook)
by (shelved 174 times as data-science)
avg rating 4.55 — 2,836 ratings — published 2017
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R for Data Science: Import, Tidy, Transform, Visualize, and Model Data R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (Kindle Edition)
by (shelved 134 times as data-science)
avg rating 4.53 — 1,235 ratings — published 2016
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Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are (Hardcover)
by (shelved 134 times as data-science)
avg rating 3.90 — 42,912 ratings — published 2017
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Python Data Science Handbook: Essential Tools for Working with Data Python Data Science Handbook: Essential Tools for Working with Data (Paperback)
by (shelved 133 times as data-science)
avg rating 4.30 — 679 ratings — published 2016
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The Art of Statistics: How to Learn from Data The Art of Statistics: How to Learn from Data (Hardcover)
by (shelved 130 times as data-science)
avg rating 4.15 — 5,804 ratings — published 2019
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Practical Statistics for Data Scientists: 50 Essential Concepts Practical Statistics for Data Scientists: 50 Essential Concepts (Paperback)
by (shelved 129 times as data-science)
avg rating 4.01 — 546 ratings — published
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Data Smart: Using Data Science to Transform Information into Insight Data Smart: Using Data Science to Transform Information into Insight (Paperback)
by (shelved 127 times as data-science)
avg rating 4.12 — 1,020 ratings — published 2013
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Doing Data Science: Straight Talk from the Frontline Doing Data Science: Straight Talk from the Frontline (Paperback)
by (shelved 125 times as data-science)
avg rating 3.73 — 567 ratings — published 2013
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The Visual Display of Quantitative Information The Visual Display of Quantitative Information (Hardcover)
by (shelved 113 times as data-science)
avg rating 4.39 — 8,717 ratings — published 1983
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Pattern Recognition and Machine Learning (Information Science and Statistics) Pattern Recognition and Machine Learning (Information Science and Statistics)
by (shelved 100 times as data-science)
avg rating 4.32 — 1,913 ratings — published
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Deep Learning Deep Learning (ebook)
by (shelved 98 times as data-science)
avg rating 4.44 — 2,147 ratings — published 2016
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Invisible Women: Data Bias in a World Designed for Men Invisible Women: Data Bias in a World Designed for Men (Hardcover)
by (shelved 95 times as data-science)
avg rating 4.33 — 175,119 ratings — published 2019
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How to Lie with Statistics How to Lie with Statistics (Paperback)
by (shelved 83 times as data-science)
avg rating 3.84 — 18,301 ratings — published 1954
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Algorithms to Live By: The Computer Science of Human Decisions Algorithms to Live By: The Computer Science of Human Decisions (Hardcover)
by (shelved 76 times as data-science)
avg rating 4.12 — 35,469 ratings — published 2016
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Introduction to Machine Learning with Python: A Guide for Data Scientists Introduction to Machine Learning with Python: A Guide for Data Scientists (Paperback)
by (shelved 75 times as data-science)
avg rating 4.33 — 602 ratings — published 2015
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Designing Data-Intensive Applications Designing Data-Intensive Applications (ebook)
by (shelved 75 times as data-science)
avg rating 4.69 — 10,863 ratings — published 2015
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Deep Learning with Python Deep Learning with Python (Paperback)
by (shelved 74 times as data-science)
avg rating 4.57 — 1,428 ratings — published 2017
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The Hundred-Page Machine Learning Book The Hundred-Page Machine Learning Book (Paperback)
by (shelved 72 times as data-science)
avg rating 4.25 — 1,470 ratings — published
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Superforecasting: The Art and Science of Prediction Superforecasting: The Art and Science of Prediction (Hardcover)
by (shelved 69 times as data-science)
avg rating 4.08 — 22,592 ratings — published 2015
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Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python (Paperback)
by (shelved 68 times as data-science)
avg rating 4.21 — 261 ratings — published
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Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (Paperback)
by (shelved 66 times as data-science)
avg rating 3.67 — 2,126 ratings — published 2013
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The Book of Why: The New Science of Cause and Effect The Book of Why: The New Science of Cause and Effect (Hardcover)
by (shelved 65 times as data-science)
avg rating 3.93 — 6,704 ratings — published 2018
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Big Data: A Revolution That Will Transform How We Live, Work, and Think 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 — 8,686 ratings — published 2013
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Applied Predictive Modeling Applied Predictive Modeling (Hardcover)
by (shelved 61 times as data-science)
avg rating 4.40 — 345 ratings — published 2013
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How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers (Paperback)
by (shelved 59 times as data-science)
avg rating 4.11 — 8,406 ratings — published 2020
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The Art of Data Science: A Guide for Anyone Who Works with Data The Art of Data Science: A Guide for Anyone Who Works with Data (ebook)
by (shelved 59 times as data-science)
avg rating 3.70 — 300 ratings — published 2015
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Lean Analytics: Use Data to Build a Better Startup Faster Lean Analytics: Use Data to Build a Better Startup Faster (Hardcover)
by (shelved 58 times as data-science)
avg rating 4.11 — 8,237 ratings — published 2013
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Dataclysm: Who We Are (When We Think No One's Looking) Dataclysm: Who We Are (When We Think No One's Looking)
by (shelved 56 times as data-science)
avg rating 3.73 — 12,509 ratings — published 2014
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Think Stats Think Stats (Paperback)
by (shelved 56 times as data-science)
avg rating 3.65 — 466 ratings — published 2011
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Python Machine Learning Python Machine Learning (Paperback)
by (shelved 53 times as data-science)
avg rating 4.24 — 759 ratings — published 2015
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The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World (Hardcover)
by (shelved 50 times as data-science)
avg rating 3.73 — 6,499 ratings — published 2015
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Machine Learning: A Probabilistic Perspective Machine Learning: A Probabilistic Perspective (Hardcover)
by (shelved 48 times as data-science)
avg rating 4.34 — 522 ratings — published
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Data Analysis with Open Source Tools: A Hands-On Guide for Programmers and Data Scientists 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
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Forecasting: principles and practice Forecasting: principles and practice (Paperback)
by (shelved 42 times as data-science)
avg rating 4.39 — 318 ratings — published 2013
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Statistics Done Wrong: The Woefully Complete Guide Statistics Done Wrong: The Woefully Complete Guide (Paperback)
by (shelved 42 times as data-science)
avg rating 4.19 — 1,098 ratings — published 2013
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Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications (Paperback)
by (shelved 41 times as data-science)
avg rating 4.44 — 1,110 ratings — published 2022
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Mathematics for Machine Learning: 1st Edition Mathematics for Machine Learning: 1st Edition (Kindle Edition)
by (shelved 41 times as data-science)
avg rating 4.33 — 260 ratings — published
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Factfulness: Ten Reasons We're Wrong About the World – and Why Things Are Better Than You Think 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 — 204,147 ratings — published 2018
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Numsense! Data Science for the Layman: No Math Added Numsense! Data Science for the Layman: No Math Added (Kindle Edition)
by (shelved 41 times as data-science)
avg rating 4.14 — 622 ratings — published
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Bayesian Data Analysis Bayesian Data Analysis (Hardcover)
by (shelved 41 times as data-science)
avg rating 4.21 — 541 ratings — published 1995
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Artificial Intelligence: A Modern Approach Artificial Intelligence: A Modern Approach (Hardcover)
by (shelved 39 times as data-science)
avg rating 4.21 — 4,474 ratings — published 1994
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“In the midst of World War II, Quincy Wright, a leader in the quantitative study of war, noted that people view war from contrasting perspectives:

“To some it is a plague to be eliminated; to others, a crime which ought to be punished; to still others, it is an anachronism which no longer serves any purpose. On the other hand, there are some who take a more receptive attitude toward war, and regard it as an adventure which may be interesting, an instrument which may be legitimate and appropriate, or a condition of existence for which one must be prepared”

Despite the millions of people who died in that most deadly war, and despite widespread avowals for peace, war remains as a mechanism of conflict resolution.

Given the prevalence of war, the importance of war, and the enormous costs it entails, one would assume that substantial efforts would have been made to comprehensively study war. However, the systematic study of war is a relatively recent phenomenon. Generally, wars have been studied as historically unique events, which are generally utilized only as analogies or examples of failed or successful policies. There has been resistance to conceptualizing wars as events that can be studied in the aggregate in ways that might reveal patterns in war or its causes. For instance, in the United States there is no governmental department of peace with funding to scientifically study ways to prevent war, unlike the millions of dollars that the government allocates to the scientific study of disease prevention. This reluctance has even been common within the peace community, where it is more common to deplore war than to systematically figure out what to do to prevent it. Consequently, many government officials and citizens have supported decisions to go to war without having done their due diligence in studying war, without fully understanding its causes and consequences.

The COW Project has produced a number of interesting observations about wars. For instance, an important early finding concerned the process of starting wars. A country’s goal in going to war is usually to win. Conventional wisdom was that the probability of success could be increased by striking first. However, a study found that the rate of victory for initiators of inter-state wars (or wars between two countries) was declining: “Until 1910 about 80 percent of all interstate wars were won by the states that had initiated them. . . . In the wars from 1911 through 1965, however, only about 40 percent of the war initiators won.”

A recent update of this analysis found that “pre-1900, war initiators won 73% of wars. Since 1945 the win rate is 33%.”. In civil war the probability of success for the initiators is even lower. Most rebel groups, which are generally the initiators in these wars, lose. The government wins 57 percent of the civil wars that last less than a year and 78 percent of the civil wars lasting one to five years.

So, it would seem that those initiating civil and inter-state wars were not able to consistently anticipate victory. Instead, the decision to go to war frequently appears less than rational. Leaders have brought on great carnage with no guarantee of success, frequently with no clear goals, and often with no real appreciation of the war’s ultimate costs. This conclusion is not new. Studying the outbreak of the first carefully documented war, which occurred some 2,500 years ago in Greece, historian Donald Kagan concluded:

“The Peloponnesian War was not caused by impersonal forces, unless anger, fear, undue optimism, stubbornness, jealousy, bad judgment and lack of foresight are impersonal forces. It was caused by men who made bad decisions in difficult circumstances.”

Of course, wars may also serve leaders’ individual goals, such as gaining or retaining power. Nonetheless, the very government officials who start a war are sometimes not even sure how or why a war started.”
Frank Wayman, Resort to War: 1816 - 2007

“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.”
Damian Mingle

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