100 Best Data Science Books of All Time
We've researched and ranked the best data science books in the world, based on recommendations from world experts, sales data, and millions of reader ratings. Learn more
Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll... more
Recommended by Kirk Borne, and 1 others. Kirk BorneGreat book for Business Analytics and for building #AnalyticThinking >> “#DataScience for Business — What You Need to Know about #DataMining and Data-Analytic Thinking”: https://t.co/e9rAFnVYYQ #BigData #MachineLearning #DataStrategy #AnalyticsStrategy #Algorithms https://t.co/yEblfU2MZd (Source)
Recommended by Roger D. Peng, and 1 others. Roger D. PengThis book is written by a powerhouse of authors in the machine learning community, true authorities in the field. But beyond that, they’re also great writers. (Source)
Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal... more
Recommended by Roger D. Peng, and 1 others. Roger D. PengIt’s important to think in terms of what your audience needs, and what would be best for them among the many choices you could make when analysing data. (Source)
Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive... more
But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.
Data science is little more than using straight-forward steps to process raw data into... more
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data... more
Thorsten HellerThe Best #book to Start your #DataScience Journey - Towards #DataScience https://t.co/D8PlkkSxw6 by @benthecoder1 (Source)
Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing... more
Recommended by Kirk Borne, and 2 others. Kirk Borne✨🎉🌟Must see this >> Free #Python #DataScience Coding book series for #DataScientists ...via @DataScienceCtrl Go to https://t.co/To10VVZzIl ——————— #abdsc #BigData #MachineLearning #AI #DeepLearning #BeDataBrilliant #DataLiteracy https://t.co/Msuo1jiZSm (Source)
New York Times Bestseller
"Not so different in spirit from the way public intellectuals like John Kenneth Galbraith once shaped discussions of economic policy and public figures like Walter Cronkite helped sway opinion on the Vietnam War…could turn out to be one of the more momentous books of the decade."
-New York Times Book Review
"Nate Silver's The Signal and the Noise is The Soul of a New Machine for the 21st century."
-Rachel Maddow, author of Drift
"A serious... more
Recommended by Bill Gates, and 1 others. Bill GatesAnyone interested in politics may be attracted to Nate Silver’s The Signal and the Noise: Why So Many Predictions Fail—but Some Don't. Silver is the New York Times columnist who got a lot of attention last fall for predicting—accurately, as it turned out–the results of the U.S. presidential election. This book actually came out before the election, though, and it’s about predictions in many... (Source)
When asked simple questions about global trends—what percentage of the world’s population live in poverty; why the world’s population is increasing; how many girls finish school—we systematically get the answers wrong. So wrong that a chimpanzee choosing answers at random will consistently outguess teachers, journalists, Nobel laureates, and investment bankers.
In Factfulness, Professor of International Health and global TED phenomenon... more
Barack ObamaAs 2018 draws to a close, I’m continuing a favorite tradition of mine and sharing my year-end lists. It gives me a moment to pause and reflect on the year through the books I found most thought-provoking, inspiring, or just plain loved. It also gives me a chance to highlight talented authors – some who are household names and others who you may not have heard of before. Here’s my best of 2018... (Source)
Bill GatesThis was a breakthrough to me. The framework Hans enunciates is one that took me decades of working in global development to create for myself, and I could have never expressed it in such a clear way. I’m going to try to use this model moving forward. (Source)
Nigel WarburtonIt’s an interesting book, it’s very challenging. It may be over-optimistic. But it does have this startling effect on the readers of challenging widely held assumptions. It’s a plea to look at the empirical data, and not just assume that you know how things are now. (Source)
New York Times Bestseller
A former Wall Street quant sounds an alarm on the mathematical models that pervade modern life -- and threaten to rip apart our social fabric
We live in the age of the algorithm. Increasingly, the decisions that affect our lives--where we go to school, whether we get a car loan, how much we pay for health insurance--are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is... more
Paula BoddingtonHow the use of algorithms has affected people’s lives and occasionally ruined them. (Source)
Ramesh SrinivasanThis book is a really fantastic analysis of how quantification, the collection of data, the modelling around data, the predictions made by using data, the algorithmic and quantifiable ways of predicting behaviour based on data, are all built by elites for elites and end up, quite frankly, screwing over everybody else. (Source)
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions.
By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we... more
Jj. Omojuwa@SympLySimi Lol. Read this book. You’d love it. https://t.co/d2cLOyoiZ9 (Source)
Ron FournierJust finished, “Everybody Lies” by @SethS_D, which in addition to being a tremendous education on Big Data, includes the best conclusion to a non-fiction book I’ve ever read. Read it. -30- (Source)
Carol DweckYou would think that the relationship between training and skill would be utterly obvious in sports, but apparently it isn’t. (Source)
David PapineauIt’s a parable of the disinclination of people in general to base their practices on evidence, a parable for evidence-based policy in general. (Source)
By using concrete examples, minimal theory, and two production-ready Python frameworks-scikit-learn and TensorFlow-author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple...
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Recommended by Mark Tabladillo, and 1 others. Mark TabladilloBook to Start You on Machine Learning - KDnuggets https://t.co/19fdX59b0d This book is “Hands-On Machine Learning with Scikit-Learn & TensorFlow”. each new revision has become an even better version of one of the best in-depth resources to learn Machine Learning by doing. https://t.co/ujyUH3xU3e (Source)
This is the... more
Michael OkudaEdward Tufte's classic book, The Visual Display of Quantitative Information is a fascinating, surprisingly readable treatise for anyone interested in infographics. When I hired artists for the Star Trek graphics dept, I sometimes asked them to read it.https://t.co/cK4GQqBDxp (Source)
The astonishing success of Google was a black swan; so was 9/11. For Nassim Nicholas Taleb, black swans underlie almost everything about our world, from the rise of religions to events in our own personal lives.
Why do we not acknowledge the phenomenon of black swans until after they occur? Part of the answer, according to... more
Bill Gates[On Bill Gates's reading list in 2012.] (Source)
Jeff Bezos[From the book "The Everything Store: and the Age of Amazon"] “The scholar argues that people are wired to see patterns in chaos while remaining blind to unpredictable events, with massive consequences. Experimentation and empiricism trumps the easy and obvious narrative,” Stone writes. (Source)
James AltucherAnd throw in “The Black Swan” and “Fooled by Randomness”. “Fragile” means if you hit something might break. “Resilient” means if you hit something, it will stay the same. On my podcast Nassim discusses “Antifragility” – building a system, even on that works for you on a personal level, where you if you harm your self in some way it becomes stronger. That podcast changed my life He discusses... (Source)
Winner of the National Academy of Sciences Best Book Award in 2012
Selected by the New York Times Book Review as one of the best books of 2011
A Globe and Mail Best Books of the Year 2011 Title
One of The Economist's 2011 Books of the Year
One of The Wall Street Journal's Best Nonfiction Books of the Year 2011
2013 Presidential Medal of Freedom Recipient
In the international bestseller, Thinking, Fast and Slow, Daniel Kahneman, the renowned psychologist and winner of the Nobel... more
Barack ObamaA few months ago, Mr. Obama read “Thinking, Fast and Slow,” by Daniel Kahneman, about how people make decisions — quick, instinctive thinking versus slower, contemplative deliberation. For Mr. Obama, a deliberator in an instinctive business, this may be as instructive as any political science text. (Source)
Bill Gates[On Bill Gates's reading list in 2012.] (Source)
Marc AndreessenCaptivating dive into human decision making, marred by inclusion of several/many? psychology studies that fail to replicate. Will stand as a cautionary tale? (Source)
These may not sound like typical questions for an economist to ask. But Steven D. Levitt is not a typical economist. He is a much heralded scholar who studies the stuff and riddles of everyday life -- from cheating and crime to sports and child rearing -- and whose... more
Malcolm GladwellI don’t need to say much here. This book invented an entire genre. Economics was never supposed to be this entertaining. (Source)
Daymond JohnI love newer books like [this book]. (Source)
James Altucher[James Altucher recommended this book on the podcast "The Tim Ferriss Show".] (Source)
In April 1956, a refitted oil tanker carried fifty-eight shipping containers from Newark to Houston. From that modest beginning, container shipping developed into a huge industry that made the boom in global trade possible. "The Box" tells the dramatic story of the container's creation, the decade of struggle before it was widely adopted, and the sweeping economic consequences of the sharp fall in transportation costs that containerization brought about.
Published on the fiftieth anniversary of the first container voyage, this is the first comprehensive history of the shipping... more
Bill GatesI picked this one up after seeing it on a Wall Street Journal list of good books for investors. It was first published in 1954, but it doesn’t feel dated (aside from a few anachronistic examples—it has been a long time since bread cost 5 cents a loaf in the United States). In fact, I’d say it’s more relevant than ever. One chapter shows you how visuals can be used to exaggerate trends and give... (Source)
Tobi LütkeWe all live in Malcolm’s world because the shipping container has been hugely influential in history. (Source)
Jason ZweigThis is a terrific introduction to critical thinking about statistics, for people who haven’t taken a class in statistics. (Source)
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the...
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Recommended by Nassim Nicholas Taleb, and 1 others. Nassim Nicholas TalebVery comprehensive, sufficiently technical to get most of the plumbing behind machine learning. Very useful as a reference book (actually, there is no other complete reference book). The authors are the real thing (Tibshirani is the one behind the LASSO regularization technique). Uses some mathematical statistics without the burdens of measure theory and avoids the obvious but complicated... (Source)
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R programming language, and have some exposure to... more
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by... more
Nassim Nicholas TalebVery clear exposition, does the math without getting lost in the details. Although many of the concepts of the introductory first 100 pages can be found elsewhere, they are presented with remarkable cut-to-the-chase clarity. (Source)
Satya NadellaElon Musk and Facebook AI chief Yann LeCun have praised this textbook on one of software’s most promising frontiers. After its publication, Microsoft signed up coauthor Bengio, a pioneer in machine learning, as an adviser (Source)
In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re... more
This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur... more
Ola OlusogaLike Charlie Munger once said: “I’ve long believed that a certain system - which almost any intelligent person can learn - works way better than the systems most people use [to understand the world]. What you need is a latticework of mental models in your head. And, with that system, things gradually fit together in a way that enhances cognition. Just as multiple factors shape every system,... (Source)
Concise and to the point — the book can be read during a week. During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.
Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.
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Recommended by Kirk Borne, and 1 others. Kirk BorneRecent top-selling books in #AI & #MachineLearning: https://t.co/Ij9I7SzR4d ————— #BigData #DataScience #DataMining #Algorithms #PredictiveAnalytics #Python ————— ...in the TOP 10: 1)The Hundred-Page ML Book: https://t.co/dQ7nP6gwP0 2)Hands-on ML with...: https://t.co/Y0Iz3GbtGP https://t.co/72rAFN1FwW (Source)
Recommended by Kirk Borne, and 1 others. Kirk BorneFind more than 40 useful #PredictiveModeling articles here at @DataScienceCtrl https://t.co/KdcvLRffRk #abdsc ———— #BigData #DataScience #AI #MachineLearning #Forecasting #Statistics #PredictiveAnalytics ——— +This is the best book on the subject: https://t.co/SmsepmniHi https://t.co/amBJHCJSHN (Source)
In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of... more
An audacious, irreverent investigation of human behavior—and a first look at a revolution in the making
Our personal data has been used to spy on us, hire and fire us, and sell us stuff we don’t need. In Dataclysm, Christian Rudder uses it to show us who we truly are.
For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and... more
Recommended by Elad Yom-Tov, and 1 others. Elad Yom-TovChristian Rudder was the chief scientist of a dating website, OK Cupid. (Source)
All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same... more
Doug McMillonHere are some of my favorite reads from 2017. Lots of friends and colleagues send me book suggestions and it's impossible to squeeze them all in. I continue to be super curious about how digital and tech are enabling people to transform our lives but I try to read a good mix of books that apply to a variety of areas and stretch my thinking more broadly. (Source)
Sriram Krishnan@rabois @nealkhosla Yes! Love that book (Source)
Chris OliverThis is a great book talking about how you can use computer science to help you make decisions in life. How do you know when to make a decision on the perfect house? Car? etc? It helps you apply algorithms to making those decisions optimally without getting lost. (Source)
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.
The coverage combines breadth and depth, offering... more
Recommended by Kirk Borne, and 1 others. Kirk Borne[Book] #MachineLearning — a Probabilistic Perspective: https://t.co/wAZwLoUFGF ———— #BigData #Statistics #DataScience #DeepLearning #AI #Algorithms #StatisticalLiteracy #Mathematics #abdsc ——— ⬇Get this brilliant 1100-page 28-chapter highly-rated book: https://t.co/Tm2zchpHSu https://t.co/jprUDdzkj8 (Source)
Which paint color is most likely to tell you that a used car is in good shape? How can officials identify the most dangerous New York City manholes before they explode? And how did Google searches predict the spread of the H1N1 flu outbreak?
The key to answering these questions, and many more, is big data. “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw... more
Many of the most innovative breakthroughs and exciting new technologies can be attributed to applications of machine learning. We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search... more
An Economist Best Book of 2015
"The most important book on decision making since Daniel Kahneman's Thinking, Fast and Slow."
—Jason Zweig, The Wall Street Journal
Everyone would benefit from seeing further into the future, whether buying stocks, crafting policy, launching a new product, or simply planning the week’s meals. Unfortunately, people tend to be terrible forecasters. As Wharton professor Philip Tetlock showed in a landmark 2005 study, even... more
Sheil KapadiaRead the book Superforecasting, had a great conversation with @bcmassey and came up with seven ideas for how NFL teams can try to find small edges during the draft process. Would love to hear feedback on this one. https://t.co/PdN1fKCagl (Source)
Julia Galef[Has] some good advice on how to improve your ability to make accurate predictions. (Source)
Proven approaches such as service-oriented and event-driven architectures are joined by newer techniques such as microservices, reactive architectures, DevOps, and stream processing. Many of these patterns are successful by themselves, but as this practical ebook demonstrates, they provide a more holistic and compelling approach when applied together.
Author Ben Stopford explains how service-based... more
Kevin RoseThe master when it comes to taking complicated data and turning it into beautiful charts and graphs that are easy to understand. If you’re into graphic design, print design, web design, you name it, you’re going to get some really good information and how tos out of these books. He has a whole series of these books. (Source)
"The Freakonomics of big data." --Stein Kretsinger, founding executive of Advertising.com
Award-winning - Used by over 30 universities - Translated into 9 languages
An introduction for everyone. In this rich, fascinating -- surprisingly accessible -- introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a "how to" for hands-on... more
You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the... more
Recommended by Francesco Marconi, and 1 others. Francesco MarconiTop programming languages ranked by its annual search engine popularity. Python has gained momentum because of its importance to machine learning development. At @WSJ we are using it to build tools for journalists. Tip: this is a great book for anyone who wants to get started! https://t.co/ZsHjqB5gvC (Source)
Recommended by Tim @Realscientists, and 1 others. Tim @RealscientistsIf you are interested in learning programming, there are lots of great tutorials. For data analysis, R and the R 4 data science book is a great way to go https://t.co/zezYpG0TRL, and for general R syntax, there is the swirl learning package https://t.co/Tzfpnlgo3O /20 (Source)
Every day, at work, home, and school, we are bombarded with vast amounts of free data collected and shared by everyone and everything from our co-workers to our calorie counters. In this highly anticipated follow-up to The Functional Art--Alberto Cairo's foundational guide to understanding information graphics and visualization--the respected data visualization professor explains in clear terms how to work with data, discover the stories hidden within, and share those stories with the world in... more
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
Along the way, you'll experiment... more
In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and... more
Recommended by Vinod Khosla, and 1 others. Vinod KhoslaIf you want speculation about what the master AI might need (one view). For a slightly more technical read, I’d suggest Ian Goodfellows Deep Learning. (Source)
Invisible Women shows us how, in a world largely built for and by men, we are systematically ignoring half the population. It exposes the gender data gap – a gap in our knowledge that is at the root of perpetual, systemic discrimination against... more
Konnie Huq@FenTiger697 @WokingAmnesty @CCriadoPerez @Hatchards @radioleary Brilliant book by the brilliant @CCriadoPerez 😍 (Source)
Feminist Next Door@Rockmedia Awesome book (Source)
Nigel ShadboltInvisible Women is an exposé of just how much of the world around us is designed around the default male. Deploying a huge range of data and examples, Caroline Criado Perez, who is a writer, broadcaster and award winning campaigner, presents on overwhelming case for change. Every page is full of facts and data that support her fundamental contention that in a world built for and by men, gender... (Source)
Now in a striking new hardcover edition, Fooled by Randomness is the word-of-mouth sensation that will change the way you think about business and the world. Nassim Nicholas Taleb–veteran trader, renowned risk expert, polymathic scholar,... more
James AltucherAnd throw in “The Black Swan” and “Fooled by Randomness”. “Fragile” means if you hit something might break. “Resilient” means if you hit something, it will stay the same. On my podcast Nassim discusses “Antifragility” – building a system, even on that works for you on a personal level, where you if you harm your self in some way it becomes stronger. That podcast changed my life He discusses... (Source)
Howard MarksReally about how much randomness there is in our world. (Source)
Anant JainThe five-book series, "Incerto", by Nassim Nicholas Taleb has had a profound impact on how I think about the world. There’s some overlap across the books — but you'll likely find the repetition helpful in retaining the content better. (Source)
Programming Collective Intelligence takes you into the world of machine learning... more
Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R.
The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn:
The fundamentals of R, including standard data types... more
"Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality--the study of cause and effect--on a firm scientific basis. His work explains how we can know easy things,... more
D.a. Wallach@EricTopol @yudapearl @bschoelkopf @MPI_IS I love @yudapearl 's book so much! Profound, heterodox. (Source)
Kirk Borne.@yudapearl wrote the awesome "Book of Why", but he recommends this fun and less #mathematics-heavy read >> his #AI lecture given in 1999: https://t.co/kNYIoJ8qcY #DataScience #MachineLearning #Statistics #BookofWhy #Causalinference #Bayes https://t.co/CNQlKP8cU3 (Source)
The powers that surveil us do more than simply store this information. Corporations use surveillance to manipulate not only the news articles and advertisements we each see, but also the... more
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
Packed with examples and exercises, Natural... more
Yuval Noah HarariA superb and very timely survey of the impact of AI on the geopolitical system, the job market and human society. (Source)
Arianna HuffingtonKai-Fu Lee's experience as an AI pioneer, top investor, and cancer survivor has led to this brilliant book about global technology. AI Superpowers gives us a guide to a future that celebrates all the benefits that AI will bring, while cultivating what is unique about our humanity. It’s one of those books you read and think, ‘Why are people reading any other book right now when this is so clearly... (Source)
Satya NadellaKai-Fu Lee's smart analysis on human-AI coexistence is clear-eyed and a must-read. We must look deep within ourselves for the values and wisdom to guide AI's development. (Source)
Recommended by Roger D. Peng, and 1 others. Roger D. PengThis book is about how best to present data to other people, what are the tools that you can use, and the types of visualizations that you can make. (Source)
The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. If machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful--possibly beyond our control. As the fate of the... more
Maria RamosRamos will take the summer to examine some of the questions weighing more heavily on humankind as we contemplate our collective future: what happens when we can write our own genetic codes, and what happens when we create technology that is meaningfully more intelligent than us. The Gene: An Intimate History—Siddhartha Mukherjee Superintelligence: Paths, Dangers, Strategies—Nick Bostrom The... (Source)
Will MacAskillI picked this book because the possibility of us developing human-level artificial intelligence, and from there superintelligence—an artificial agent that is considerably more intelligent than we are—is at least a contender for the most important issue in the next two centuries. Bostrom’s book has been very influential in effective altruism, lots of people work on artificial intelligence in order... (Source)
Marius Ciuchete Pauneval(ez_write_tag([[250,250],'theceolibrary_com-large-mobile-banner-2','ezslot_5',164,'0','1'])); Question: Was there a moment, specifically, when something you read in a book helped you? Answer: Yes there was. In fact, I can remember two separate sentences from two different books: The first one comes from “The Design of Everyday Things” by Don Norman. It says: “great design will help... (Source)
Grey BakerI mainly read to decompress and change my state of mind, so it’s hard to point to an insight I read that helped me. Reading fiction has pulled me out of a bad mood more times than I can count, though, and always reenergises me to attack problems that had stumped me again. That said, I read and loved Norman Norman’s “The Design of Everyday Things”, and it’s helped me think through design problems... (Source)
Kaci LambeThese three books are about how people actually use design in their lives. They helped me understand this very basic idea: There are no dumb users, only bad designers. Take the time to create based on how your design will be interacted with. Test it. Iterate. That's how you become a good designer. (Source)
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
In The Black Swan Taleb outlined a problem; in Antifragile he offers a definitive solution: how to gain from disorder and chaos while being protected from fragilities and adverse events. For what he calls the "antifragile" is one step beyond robust, as it benefits from adversity, uncertainty and stressors, just as human bones get stronger when subjected to stress and tension.
Taleb stands... more
James AltucherYou ask about success. To be successful you have to avoid being “fragile” – the idea that if something hurts you, you let collapse completely. You also have to avoid simply being resilient. Bouncing back is not enough. Antifragile is when something tries to hurt you and you come back stronger. That is real life business. That is real life success. Nassim focuses on the economy. But when I read... (Source)
Marvin Liaoeval(ez_write_tag([[250,250],'theceolibrary_com-leader-2','ezslot_7',164,'0','1'])); My list would be (besides the ones I mentioned in answer to the previous question) both business & Fiction/Sci-Fi and ones I personally found helpful to myself. The business books explain just exactly how business, work & investing are in reality & how to think properly & differentiate yourself. On... (Source)
Vlad TenevThe general concept is applicable to many fields beyond biology, for instance finance, economics and monetary policy. (Source)
"Statistics Done Wrong" comes to the rescue with cautionary tales of all-too-common statistical fallacies. It'll help you see where and why researchers often go wrong and teach you the best practices for avoiding their mistakes.
In this... more
In this 3rd edition, Steve returns with fresh perspective to reexamine the principles that made Don’t Make Me Think a classic-–with updated examples and a new chapter on mobile usability. And it’s still short, profusely illustrated…and best of all–fun to read.
If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web... more
Chris GowardHere are some of the books that have been very impactful for me, or taught me a new way of thinking: [...] Don't Make Me Think. (Source)
Nicolae AndronicI’m a technical guy. I studied the IT field and did software development for a long time until I discovered the business world. So the path for me is to slowly adapt from the clear, technical world, to the fuzzy, way more complex, business world. All the books that I recommend help this transition. “Don’t Make Me Think” - Steve Krug: for seeing software with the eyes of the user. (Source)
Nick GanjuAbout usability and making software and user interfaces that are friendly to people. (Source)
Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to... more
Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases faced while collecting, curating, and analyzing the data crucial to the success of businesses. Readers will apply the R programming... more
Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R... more
Reference text for data science in top universities like Stanford and Cambridge. Sold in over 85 countries and translated into more than 5 languages.
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This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and... more
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
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Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you're ready to get started.
Use R's default graphics for quick exploration of data
Create a... more
You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools... more
Stronger focus on MCMC Revision of the computational advice in Part... more
The math we learn in school can seem like a dull set of rules, laid down by the ancients and not to be questioned. In How Not to Be Wrong, Jordan Ellenberg shows us how terribly limiting this view is: Math isn’t confined to abstract incidents that never occur in real life, but rather touches everything we do—the whole world is shot through with it.
Math allows us to see the hidden structures underneath the messy and... more
Bill GatesThe writing is funny, smooth, and accessible -- not what you might expect from a book about math. What Ellenberg has written is ultimately a love letter to math. If the stories he tells add up to a larger lesson, it’s that 'to do mathematics is to be, at once, touched by fire and bound by reason' -- and that there are ways in which we’re all doing math, all the time. (Source)
Auston BunsenI’ve got a few, one book that really impacted me early on as someone coming from a middle-class family was “Rich dad, Poor dad”. Since then I’ve read many books but one that really stands out is “How not to be wrong” by Jordan Ellenberg which really reignited my appetite & appreciation for math. (Source)
Nick GanjuWritten for an audience of people who have historically been intimidated by math [...] and introduces things in a very simple way, and then works up to more complex concepts. (Source)
How can we grow our prosperity through automation without leaving people lacking income or purpose? What career advice should we give today's kids? How can we make future AI systems more robust, so that they do... more
Barack ObamaAs 2018 draws to a close, I’m continuing a favorite tradition of mine and sharing my year-end lists. It gives me a moment to pause and reflect on the year through the books I found most thought-provoking, inspiring, or just plain loved. It also gives me a chance to highlight talented authors – some who are household names and others who you may not have heard of before. Here’s my best of 2018... (Source)
Bill GatesAnyone who wants to discuss how artificial intelligence is shaping the world should read this book. (Source)
The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the... more
Using everyday objects and familiar language systems such as Braille and Morse code, author Charles Petzold weaves an illuminating narrative for anyone who’s ever wondered about the secret inner life of... more
Recommended by Ana Bell, and 1 others. 
If you were accused of a crime, who would you rather decide your sentence—a mathematically consistent algorithm incapable of empathy or a compassionate human judge prone to bias and error? What if you want to buy a driverless car and must choose between one programmed to save as many lives as possible and another that prioritizes the lives of its own passengers? And would you agree to share your family’s full medical history if you were told that it would help researchers find a cure for... more
David SmithDarroch: “The best book I’ve read recently is called Hello World... It’s about the impact of algorithms across different areas... For me this was the best piece of learning I’ve done in recent months.” (Source)
Jim Al-KhaliliThe fact is, the age of AI is coming fast, and we need to be ready for it. This book will help you decide how worried you should be. (Source)
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
Recommended by Daniel H Wilson, and 1 others. Daniel H WilsonYes, Machine Learning is a textbook and I would call it the textbook for machine learning and artificial intelligence. Machine learning is just the math of teaching a machine how to solve a problem on its own, because you’re not going to be able to be there to solve it for the machine. It can be any kind of problem: it could be a robot that needs to figure out how to get from point A to point B... (Source)
Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:
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Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This... more
Recommended by Zachary Lipton, and 1 others. Zachary Lipton@innerproduct 1. Tor Lattimore Great book work on bandits (https://t.co/gttspSm40W) and work on causality + bandits (https://t.co/lkwvtEiKvE) 2. Caroline Uhler — Interesting work on causal inference + discovery, causal inference under measurement error etc (https://t.co/I3IRpwmdMd) (Source)
Through exercises in each chapter, you'll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and... more
Shannon and MIT mathematician Edward O. Thorp took the "Kelly formula" to Las Vegas. It worked. They realized that there was even more money to be made... more
Recommended by P. D. Mangan, and 1 others. P. D. Mangan@MarquisDeMarche @natstewart5 Great book. (Source)
From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models--from linear regression to random walks and far beyond--that can turn anyone into a genius. At the core of the book is Page's... more
En este nuevo libro, Leonard Mlodinow... more
David SpiegelhalterThis is a general introduction to the history of probability and the way it comes into everyday life. It intersperses the historical development with modern applications, and looks at finance, sport, gambling, lotteries and coincidences. (Source)
Gabriel CoarnaLeonard Mlodinow's "The Drunkarkd's Walk" -more precisely, the section on the "Monty Hall" problem- totally changed how I look-at/think-about probabilities and choices in general; this has impacted almost every real-life choice I've made since I read this book. (Source)
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.
Recommended by Bret Victor, and 1 others. 
Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders.
In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge... more
Recommended by Dan Davies, and 1 others. Dan Davies@amoralelite @d_spiegel It's a great book. I thought it was like coming home because I've always tried to avoid calculation due to the dyspraxia and it was just "yes, that's how you think about it" (Source)
Now, with Think Like a Freak, Steven D. Levitt and Stephen J. Dubner have written their most revolutionary book yet. With their trademark blend of captivating storytelling and unconventional analysis, they take us inside their thought process and teach us all to think a bit more productively, more creatively, more rationally—to think, that is, like a Freak.
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This book will teach you the visual... more
Jacket design: Dmitry Krasny.
Other artwork by Bonnie Scranton, Dmitry... more
R in Action is the first book to present both the R system and the use cases that make it such a compelling package for business developers. The book begins by introducing the R language, including the development environment. Focusing on practical solutions, the book also offers a crash course in practical statistics and covers elegant methods for dealing with messy and incomplete data using features of R.
About the Technology
R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It... more
to choose the best chart that fits your data;
the most effective way to communicate with decision makers when you have five minutes of their time;
how to chart... more
This is the second edition of the best selling Python book in the world. Python Crash Course, 2nd Edition is a straightforward introduction to the core of Python programming. Author Eric Matthes dispenses with the sort of tedious, unnecessary information that can get in the way of learning how to program, choosing instead to provide a foundation in general... more
Don't have time to read the top Data Science books of all time? Read Shortform summaries.
Shortform summaries help you learn 10x faster by:
- Being comprehensive: you learn the most important points in the book
- Cutting out the fluff: you focus your time on what's important to know
- Interactive exercises: apply the book's ideas to your own life with our educators' guidance.