Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics - we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us”.

Artificial intelligence does the seemingly impossible - 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 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, policy makers, investors, and entrepreneurs.

In our age of accelerating progress in so many fields, it’s easy to lose sight of the underlying innovation that makes the data analytics revolution possible. These 24 lectures introduce you to the key concepts, methods, and accomplishments of this versatile approach to problem solving. You need no expertise in mathematics to follow this exciting story. Tim Chartier, professor of mathematics and computer science, explains the basic computational techniques used in data analytics, but his focus is on how these ideas are applied and the amazing results they achieve.

James Gleick, the author of the best sellers Chaos and Genius, now brings us a work just as astonishing and masterly: A revelatory chronicle and meditation that shows how information has become the modern era’s defining quality - the blood, the fuel, the vital principle of our world. The story of information begins in a time profoundly unlike our own, when every thought and utterance vanishes as soon as it is born.

In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent - really - are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant methods of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought that led to recent achievements.

His work is cited by the world's best-known thought leaders, from Steve Jobs to Malcolm Gladwell. In this classic best seller - one of the most influential business books of all time - innovation expert Clayton Christensen shows how even the most outstanding companies can do everything right - yet still lose market leadership. Christensen explains why most companies miss out on new waves of innovation.

Most startups fail. But many of those failures are preventable. The Lean Startup is a new approach being adopted across the globe, changing the way companies are built and new products are launched.

Most people believe that the best way to motivate is with rewards like money - the carrot-and-stick approach. That's a mistake, says Daniel H. Pink (author of To Sell Is Human: The Surprising Truth About Motivating Others). In this provocative and persuasive new book, he asserts that the secret to high performance and satisfaction - at work, at school, and at home - is the deeply human need to direct our own lives, to learn and create new things, and to do better by ourselves and our world.

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Following his blockbuster biography of Steve Jobs, The Innovators is Walter Isaacson’s revealing story of the people who created the computer and the Internet. It is destined to be the standard history of the digital revolution and an indispensable guide to how innovation really happens. What were the talents that allowed certain inventors and entrepreneurs to turn their visionary ideas into disruptive realities? What led to their creative leaps? Why did some succeed and others fail?

In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very concept of the firm. AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value.

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.

The pressures on organizations to change will only increase over the next decades. Yet the methods managers have used to strengthen their companies—total quality management, reengineering, right sizing, restructuring, cultural change, and turnarounds—routinely fall short. In Leading Change, Kotter identifies an eight-step process that every company must go through to achieve its goal, and shows where and how people—good people—often derail.

Work with data like a pro using this guide that breaks down how to organize, apply, and most importantly, understand what you are analyzing in order to become a true data ninja.

In The Second Machine Age, Andrew McAfee and Erik Brynjolfsson predicted some of the far-reaching effects of digital technologies on our lives and businesses. Now they’ve written a guide to help listeners make the most of our collective future. Machine | Platform | Crowd outlines the opportunities and challenges inherent in the science fiction technologies that have come to life in recent years, like self-driving cars and 3D printers, online platforms for renting outfits and scheduling workouts, or crowd-sourced medical research and financial instruments.

What to Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on artificial intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans, it raises profound questions on the future of work and how companies compete.

Many people today are so dazzled by the long-term potential for artificial intelligence that they overlook the much clearer and more immediate potential for a new form of "collective intelligence": the intelligence of groups of people and computers working together. In Superminds, Thomas Malone explains what we need to do to take advantage of this potential. Groundbreaking and utterly fascinating, Superminds will change the way you work - both with others and with computers - for the better.

Artificial intelligence is changing our world faster than we can imagine, and it will impact every area of our lives. And this is happening whether we like it or not. You might have heard that many jobs will be replaced by automation and robots, but did you also know that at the same time a huge number of new jobs will be created by AI? This book covers many fascinating and timely topics related to artificial intelligence, including: self-driving cars, robots, chatbots, and how AI will impact the job market, business processes, and entire industries, just to name a few.

This book predicts the decline of today's professions and describes the people and systems that will replace them. In an Internet society, according to Richard Susskind and Daniel Susskind, we will neither need nor want doctors, teachers, accountants, architects, the clergy, consultants, lawyers, and many others to work as they did in the 20th century.

A fascinating guided tour of the complex, fast-moving, and influential world of algorithms - what they are, why they’re such powerful predictors of human behavior, and where they’re headed next. Algorithms exert an extraordinary level of influence on our everyday lives - from dating websites and financial trading floors, through to online retailing and internet searches - Google's search algorithm is now a more closely guarded commercial secret than the recipe for Coca-Cola.

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.

Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now - in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on?

Coal, iron ore, and oil were the key productive assets that fueled the Industrial Revolution. Today data is the vital raw material of the information economy. The explosive abundance of this digital asset, more than doubling every two years, is creating a new world of opportunity and challenge. Data-ism is about this next phase, in which vast, Internet-scale data sets are used for discovery and prediction in virtually every field. It is a journey across this emerging world with people, illuminating narrative examples, and insights.

What do Google, Snapchat, Tinder, Amazon, and Uber have in common, besides soaring market share? They're platforms - a new business model that has quietly become the only game in town. A platform, by definition, creates value by facilitating an exchange between two or more interdependent groups. So, rather than making things, they simply connect people. The advent of mobile computing and its ubiquitous connectivity have forever altered how we interact with each other. Yet, few people truly grasp the radical structural shifts of the last 10 years.

Today, not only is everything digital getting faster, cheaper, and smaller at an exponential rate, we also have the Internet. When these two revolutions - one in technology and the other in communications - joined, an explosive force was unleashed that changed the very nature of innovation. And with any change, we have seen many strategic blunders and extraordinary learning curves along the way.

When most of us think about artificial intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that artificial intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate.

Winning with Data explores the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect. Authors Tomasz Tunguz and Frank Bien draw on extensive background in big data, business intelligence, and business strategy to provide a blueprint for companies looking to move head-on into the data wave. Instrumentation is discussed in detail, but the core of the change is in the culture.

The widening gap between rich and poor means dealing with one big, uncomfortable truth: If you're not at the top, you're at the bottom. The global labor market is changing radically thanks to growth at the high end and the low. About three quarters of the jobs created in the United States since the great recession pay only a bit more than minimum wage. Still, the United States has more millionaires and billionaires than any country ever, and we continue to mint them.

We used to know how to know. We got our answers from books or experts. We'd nail down the facts and move on. But in the Internet age, knowledge has moved onto networks. There's more knowledge than ever, of course, but it's different. Topics have no boundaries, and nobody agrees on anything.Yet this is the greatest time in history to be a knowledge seeker - if you know how.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we can get a job or a loan, how much we pay for health insurance—are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.

From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.

AI expert Yorick Wilks takes a journey through the history of artificial intelligence up to the present day, examining its origins, controversies, and achievements, as well as looking into just how it works. He also considers the future, assessing whether these technologies could menace our way of life and how we are all likely to benefit from AI applications in the years to come.

We're at an inflection point in data, where our data management solutions no longer match the complexity of organizations, the proliferation of data sources, and the scope of our aspirations to get value from data with AI and analytics. In this practical book, Zhamak Dehghani introduces data mesh, a decentralized sociotechnical paradigm drawn from modern distributed architecture that provides a new approach to sourcing, sharing, accessing, and managing analytical data at scale.

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.