How do I start learning artificial intelligence? -16 BEST Books On A.I.

we’ll try to answer the following questions using 16 best books on A.I:1)How do I start learning artificial intelligence?

What are the best books on A.I.?…What’s the best book to learn A.I.?….Which are the top books on A.I.?… What are the best books on machine learning?…. Which is the best book for Artificial Intelligence?…. Which is the best book for machine learning?.. Is a book considered technology?… Which Python book is best?..Who invented artificial intelligence?..How can I become better at machine learning? Is machine learning hard?.. Can I learn machine learning?..How is machine learning related to AI?

How should I learn Python?..What should I study for artificial intelligence?.. How can I start a career in artificial intelligence?..Is learning artificial intelligence easy?..Where can I study artificial intelligence?.. How long does it take to learn Python?.. What are the prerequisites for artificial intelligence?..What qualifies as artificial intelligence?..What is the study of artificial intelligence called?..What are the 3 types of AI?..What are the disadvantages of artificial intelligence?

1. Life 3.0 by Max Tegmark

In this authoritative and eye-opening book, Max Tegmark describes and illuminates the recent, path-breaking advances in Artificial Intelligence and how it is poised to overtake human intelligence. How will AI affect crime, war, justice, jobs, society and our very sense of being human? The rise of AI has the potential to transform our future more than any other technology—and there’s nobody better qualified or situated to explore that future than Max Tegmark, an MIT professor who’s helped mainstream research on how to keep AI beneficial.

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 what we want without crashing, malfunctioning or getting hacked? Should we fear an arms race in lethal autonomous weapons? Will machines eventually outsmart us at all tasks, replacing humans on the job market and perhaps altogether? Will AI help life flourish like never before or give us more power than we can handle?

What sort of future do you want? This book empowers you to join what may be the most important conversation of our time. It doesn’t shy away from the full range of viewpoints or from the most controversial issues—from superintelligence to meaning, consciousness and the ultimate physical limits on life in the cosmos.

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2. The Master Algorithm by Pedro Domingos

A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligence as flexible as our own
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 discusses what it will mean for business, science, and society. If data-ism is today’s philosophy, this book is its bible.

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3. Deep Medicine by Eric Topol

One of America’s top doctors reveals how AI will empower physicians and revolutionize patient care medicine has become inhuman, to disastrous effect. The doctor-patient relationship–the heart of medicine–is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard.

Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.
  • 46 Halftones, black & white 11 Tables, black & white

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4. Prediction Machines by Ajay Agrawal, Joshua Gans and Avi Goldfarb

“What does AI mean for your business? Read this book to find out.” — Hal Varian, Chief Economist, Google

Artificial intelligence does the seemingly impossible, magically bringing machines to life–driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.

But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policymakers, investors, and entrepreneurs.

When AI is framed as a cheap prediction, its extraordinary potential becomes clear:

  • Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions.
  • Prediction tools increase productivity–operating machines, handling documents, communicating with customers.
  • Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete.

Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

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5. Ai Superpowers by Kai-fu Lee

Dr. Kai-Fu Lee—one of the world’s most respected experts on AI and China—reveals that China has suddenly caught up to the US at an astonishingly rapid and unexpected pace.  

In AI Superpowers, Kai-fu Lee argues powerfully that because of these unprecedented developments in AI, dramatic changes will be happening much sooner than many of us expected. Indeed, as the US-Sino AI competition begins to heat up, Lee urges the US and China to both accept and to embrace the great responsibilities that come with significant technological power. Most experts already say that AI will have a devastating impact on blue-collar jobs. But Lee predicts that Chinese and American AI will have a strong impact on white-collar jobs as well. Is universal basic income the solution? In Lee’s opinion, probably not.  But he provides a clear description of which jobs will be affected and how soon, which jobs can be enhanced with AI, and most importantly, how we can provide solutions to some of the most profound changes in human history that are coming soon.

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6. Machine Learning Refined by Jeremy Watt, Reza Borhani and Aggelos K. Katsagellos

Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real-world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization.  Additional resources including supplemental discussion topics, code demonstrations, and exercises can be found on the official textbook website at mlrefined.com

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7. The Book Of Why by Judea Pearl And Dana Mackenzie

A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence
 
“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, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl’s work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and a key to artificial intelligence. Anyone who wants to understand either need The Book of Why.

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8. Weapons Of Math Destruction by Cathy O’neil

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 eliminated.

But as Cathy O’Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.

Tracing the arc of a person’s life, O’Neil exposes the black box models that shape our future, both as individuals and as a society. These “weapons of math destruction” score teachers and students, sort résumés, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health.

O’Neil calls on modellers to take more responsibility for their algorithms and on policymakers to regulate their use. But in the end, it’s up to us to become savvier about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.

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9. Singularity is Near by Ray Kurzweil

“Startling in scope and bravado.” —Janet Maslin, The New York Times

“Artfully envisions a breathtakingly better world.” —Los Angeles Times

“Elaborate, smart and persuasive.” —The Boston Globe

“A pleasure to read.” —The Wall Street Journal

One of CBS News’s Best Fall Books of 2005 • Among St Louis Post-Dispatch’s Best Nonfiction Books of 2005 • One of Amazon.com’s Best Science Books of 2005

A radical and optimistic view of the future course of human development from the bestselling author of How to Create a Mind and The Age of Spiritual Machines who Bill Gates calls “the best person I know at predicting the future of artificial intelligence”

For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines, he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: the union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

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10. Superintelligence by Nick Bostrom

Superintelligence asks the questions: What happens when machines surpass humans in general intelligence? Will artificial agents save or destroy us? Nick Bostrom lays the foundation for understanding the future of humanity and intelligent life.

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 gorillas now depends more on humans than on the species itself, so would the fate of humankind depend on the actions of the machine superintelligence.

But we have one advantage: we get to make the first move. Will it be possible to construct a seed Artificial Intelligence, to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation?

This profoundly ambitious and original book breaks down a vast track of difficult intellectual terrain. After an utterly engrossing journey that takes us to the frontiers of thinking about the human condition and the future of intelligent life, we find in Nick Bostrom’s work nothing less than a reconceptualization of the essential task of our time.

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11. The Diamond Age by Neal Stephenson

Vividly imagined, stunningly prophetic, and epic in scope, The Diamond Age is a major novel from one of the most visionary writers of our time

Decades into our future, a stone’s throw from the ancient city of Shanghai, a brilliant nanotechnologist named John Percival Hackworth has just broken the rigorous moral code of his tribe, the powerful neo-Victorians. He’s made an illicit copy of a state-of-the-art interactive device called A Young Lady’s Illustrated Primer  Commissioned by an eccentric duke for his grandchild, stolen for Hackworth’s own daughter, the Primer’s purpose is to educate and raise a girl capable of thinking for herself. It performs its function superbly. Unfortunately for Hackworth, his smuggled copy has fallen into the wrong hands.

Young Nell and her brother Harv are thetes—members of the poor, tribeless class.  Neglected by their mother, Harv looks after Nell.  When he and his gang waylay a certain neo-Victorian—John Percival Hackworth—in the seamy streets of their neighbourhood, Harv brings Nell something special: the Primer.

Following the discovery of his crime, Hackworth begins an odyssey of his own. Expelled from the neo-Victorian paradise, squeezed by agents of Protocol Enforcement on one side and a Mandarin underworld crime lord on the other, he searches for an elusive figure known as the Alchemist.  His quest and Nell’s will ultimately lead them to another seeker whose fate is bound up with the Primer—a woman who holds the key to a vast, subversive information network that is destined to decode and reprogram the future of humanity.

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12. Machine Learning With Random Forests And Decision Trees by Scott Hartshorn

Machine Learning – Made Easy To Understand

If you are looking for a book to help you understand how the machine learning algorithms “Random Forest” and “Decision Trees” work behind the scenes, then this is a good book for you.  Those two algorithms are commonly used in a variety of applications including big data analysis for industry and data analysis competitions like you would find on Kaggle.

This book explains how Decision Trees work and how they can be combined into a Random Forest to reduce many of the common problems with decision trees, such as overfitting the training data.

Several Dozen Visual Examples

Equations are great for really understanding every last detail of an algorithm.  But to get a basic idea of how something works, in a way that will stick with you 6 months later, nothing beats pictures.  This book contains several dozen images which detail things such as how a decision tree picks what splits it will make, how a decision tree can overfit its data, and how multiple decision trees can be combined to form a random forest.

This Is Not A Textbook

Most books, and other information on machine learning, that I have seen fall into one of two categories, they are either textbooks that explain an algorithm in a way similar to “And then the algorithm optimizes this loss function” or they focus entirely on how to set up code to use the algorithm and how to tune the parameters.

This book takes a different approach that is based on providing simple examples of how Decision Trees and Random Forests work, and building on those examples step by step to encompass the more complicated parts of the algorithms.  The actual equations behind decision trees and random forests get explained by breaking them down and showing what each part of the equation does, and how it affects the examples in question.

Python Files & Excel File For Many Of The Examples Shown In The Book

Some topics in machine learning don’t lend themselves to equations in an Excel table.  Things like error checking or complicated conditionals are hard to replicate outside of code.  However, some topics work quite well in a spreadsheet.  Topics such as entropy and information gain, which is how a decision tree picks its splits, can be easily calculated in a spreadsheet.  The spreadsheet used to generate many of the examples in this book is available for free download, as are all of the Python scripts that ran the Random Forests & Decision Trees in this book and generated many of the plots and images.

If you are someone who learns by playing with the code and editing the data or equations to see what changes, then use those resources along with the book for a deeper understanding.

Topics Covered

The topics covered in this book are

  • An overview of decision trees and random forests
  • A manual example of how a human would classify a dataset, compared to how a decision tree would work
  • How a decision tree works, and why it is prone to overfitting
  • How decision trees get combined to form a random forest
  • How to use that random forest to classify data and make predictions
  • How to determine how many trees to use in a random forest
  • Just where does the “randomness” come from
  • Out of Bag Errors & Cross-Validation – how good of a fit did the machine learning algorithm make?
  • Gini Criteria & Entropy Criteria – how to tell which split on a decision tree is best among many possible choices
  • And More

If you want to know more about how these machine learning algorithms work but don’t need to reinvent them, this is a good book for you

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13. The Rise of the Robots by Martin Ford

Winner of the 2015 FT & McKinsey Business Book of the Year Award
New York Times Bestseller
Top Business Book of 2015 at Forbes
One of NBCNews.com 12 Notable Science and Technology Books of 2015

What are the jobs of the future? How many will there be? And who will have them? We might imagine—and hope—that today’s industrial revolution will unfold like the last: even as some jobs are eliminated, more will be created to deal with the new innovations of a new era. In Rise of the Robots, Silicon Valley entrepreneur Martin Ford argues that this is absolutely not the case. As technology continues to accelerate and machines begin taking care of themselves, fewer people will be necessary. Artificial intelligence is already well on its way to making “good jobs” obsolete: many paralegals, journalists, office workers, and even computer programmers are poised to be replaced by robots and smart software. As progress continues, blue and white-collar jobs alike will evaporate, squeezing working- and middle-class families ever further. At the same time, households are under assault from exploding costs, especially from the two major industries—education and health care—that, so far, have not been transformed by information technology. The result could well be massive unemployment and inequality as well as the implosion of the consumer economy itself.

In Rise of the Robots, Ford details what machine intelligence and robotics can accomplish, and implores employers, scholars, and policymakers alike to face the implications. The past solutions to technological disruption, especially more training and education, aren’t going to work, and we must decide, now, whether the future will see broad-based prosperity or catastrophic levels of inequality and economic insecurity. Rise of the Robots is essential reading for anyone who wants to understand what accelerating technology means for their own economic prospects—not to mention those of their children—as well as for society as a whole.

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14. Profiles Of The Future by Arthur C. Clarke

Arthur C. Clarke’s many predictions culminated in 1958 when he began a series of magazine essays that eventually became Profiles of the Future, published in book form in 1962. [73] A timetable[74] up to the year 2100 describes inventions and ideas including such things as a “global library” for 2005. The same work also contained “Clarke’s First Law” and text that became Clarke’s three laws in later editions.

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15. The Second Machine Age by Erik Brynjolfsson and Andrew McAfee

New York Times Bestseller. A “fascinating” (Thomas L. Friedman, New York Times) look at how digital technology is transforming our work and our lives.

In recent years, Google’s autonomous cars have logged thousands of miles on American highways and IBM’s Watson trounced the best human Jeopardy! players. Digital technologies―with hardware, software, and networks at their core―will in the near future diagnose diseases more accurately than doctors can, apply enormous data sets to transform retailing, and accomplish many tasks once considered uniquely human.

In The Second Machine Age MIT’s Erik Brynjolfsson and Andrew McAfee―two thinkers at the forefront of their field―reveal the forces driving the reinvention of our lives and our economy. As the full impact of digital technologies is felt, we will realize immense bounty in the form of dazzling personal technology, advanced infrastructure, and near-boundless access to the cultural items that enrich our lives.

Amid this bounty will also be wrenching change. Professions of all kinds―from lawyers to truck drivers―will be forever upended. Companies will be forced to transform or die. Recent economic indicators reflect this shift: fewer people are working, and wages are falling even as productivity and profits soar.

Drawing on years of research and up-to-the-minute trends, Brynjolfsson and McAfee identify the best strategies for survival and offer a new path to prosperity. These include revamping education so that it prepares people for the next economy instead of the last one, designing new collaborations that pair brute processing power with human ingenuity, and embracing policies that make sense in a radically transformed landscape.

A fundamentally optimistic book, The Second Machine Age alters how we think about issues of technological, societal, and economic progress.

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16. Franchise by Isaac Asimov

In the future United States where one individual is selected by computer to represent the entire national electorate in voting for the new President, ordinary Norman Muller is not sure he wants that privilege

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