Regardless of whether you are new to the subject of computerized reasoning or are knowledgeable however hoping to find more, there are huge amounts of books that will meet your requirements. We’ve filtered through the most adored of them to present to you a rundown of books that will cover numerous parts of man-made reasoning from various perspectives.
Everything from the nuts and bolts of AI to history to the eventual fate of the science is analyzed and clarified finally by the capable creators in the division.
Let’s get started…
Top 10 Best Amazon Books in Artificial Intelligence & Machine Learning
Garry Kasparov’s 1997 chess match against the IBM supercomputer Deep Blue was a watershed moment in the history of technology. It was the dawn of a new era in artificial intelligence: a machine capable of beating the reigning human champion at this most cerebral game. Kasparov reveals his astonishing side of the story for the first time.
He describes how it felt to strategize against an implacable, untiring opponent with the whole world watching, and recounts the history of machine intelligence through the microcosm of chess, considered by generations of scientific pioneers to be a key to unlocking the secrets of human and machine cognition.
Kasparov uses his unrivaled experience to look into the future of intelligent machines and sees it bright with possibility. As many critics decry artificial intelligence as a menace, particularly to human jobs, Kasparov shows how humanity can rise to new heights with the help of our most extraordinary creations, rather than fear them.
This is a story of how what it means to be human in the face of accelerating machine intelligence. It’s about trying to make computers that are smarter than we are and what happens when it goes wrong. About what creativity means when all knowledge is data that can be stored on microchips.
Or about what happens when machines can learn from their mistakes much faster than humans can. And above all, it’s about the dazzling future around the corner, how our lives might just change forever and whether you and I aren’t just thinking machines of a sort as well.
In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today’s machines so smart. Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world.
Author describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog.
He explains how artificial neural networks enable computers to perceive the world-and to play Atari video games better than humans.
IBM Watson provides fast, intelligent insight in ways that the human brain simply can’t match. Through eight varied projects, this book will help you explore the computing and analytical capabilities of IBM Watson.
The book begins by refreshing your knowledge of IBM Watson’s basic data preparation capabilities, such as adding and exploring data to prepare it for being applied to models.
By the end of this book, you’ll have learned how to develop solutions for process automation, and you’ll be able to make better data-driven decisions to deliver an excellent customer experience.
Machine learning business could be your best chance as an IT professional. This is a region in the computer world that requires specialized skills to navigate through and is an integral part of most activities happening around the world.
Machine learning is a method of data analysis that incorporates the use of algorithms that have the capabilities to learn from the data and bring about certain outcomes without the need for programming to produce such results.
The algorithms are in a position to analyze the data, make a calculation of the frequency at which parts of the data are utilized and produce results from the calculations with an objective of interacting with users automatically.
Artificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more.
Hands-On Artificial Intelligence with TensorFlow gives you a rundown of essential AI concepts and their implementation with TensorFlow, also highlighting different approaches to solving AI problems using machine learning and deep learning techniques.
By the end of this book, you will be well-versed with the essential concepts of AI and their implementation using TensorFlow.
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 second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.
In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM’s Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world.
His key recommendation: don’t go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient.
Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation.
“The Fourth Age not only discusses what the rise of A.I. will mean for us, it also forces readers to challenge their preconceptions. And it manages to do all this in a way that is both entertaining and engaging.” —The New York Times
The Fourth Age offers fascinating insight into AI, robotics, and their extraordinary implications for our species. In The Fourth Age, Byron Reese makes the case that technology has reshaped humanity just three times in history: – 100,000 years ago, we harnessed fire, which led to language. – 10,000 years ago, we developed agriculture, which led to cities and warfare.
5,000 years ago, we invented the wheel and writing, which lead to the nation state. We are now on the doorstep of a fourth change brought about by two technologies: AI and robotics.
The Fourth Age provides extraordinary background information on how we got to this point, and how-rather than what-we should think about the topics we’ll soon all be facing: machine consciousness, automation, employment, creative computers, radical life extension, artificial life, AI ethics, the future of warfare, super intelligence, and the implications of extreme prosperity.
We live in an incredible period in history. The Computer Revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before.
We fear that super-intelligent machines will decide to protect themselves by enslaving or eliminating humans. But the real danger is not that computers are smarter than us, but that we think computers are smarter than us and, so, trust computers to make important decisions for us.
The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted.
If you’re like most people, you probably believe that humans are the most intelligent animals on our planet. But there’s another kind of entity that can be far smarter: groups of people. In this groundbreaking book, Thomas Malone, the founding director of the MIT Center for Collective Intelligence, shows how groups of people working together in superminds.
Using dozens of striking examples and case studies, Malone shows how computers can help create more intelligent superminds simply by connecting humans to one another in a variety of rich, new ways.
Drawing on cutting-edge science and insights from a remarkable range of disciplines, Superminds articulates a bold — and utterly fascinating — picture of the future that will change the ways you work and live, both with other people and with computers.
How deep learning―from Google Translate to driverless cars to personal cognitive assistants―is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange.
Deep learning networks can play poker better than professional poker players and defeat a world champion at Go.
In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
“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.
But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. 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.
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.