Learning Technology

In this audiobook, you'll get a clear overview of artificial intelligence technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field.

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.

Master Artificial Intelligence in no time, even if you're a total beginner or a tech novice with our essential guide — Empower your career and simplify your daily life! Does the world of AI and machine learning seem intimidating, complex, or out of reach? Are you interested in diving into the realm of AI but have no idea where to start? Are you overwhelmed by endless information and complex terminologies that seem to make AI learning more challenging? You're not alone!

Written in an accessible style for all audiences, “How AI Will Shape Our Future” anchors listeners in the history and evolution of Artificial Intelligence, laying the groundwork for a deeper understanding of its trajectory. This equips listeners to engage more thoughtfully with the book’s central theme: What should societies expect from AI in the decades ahead? How does AI actually function? What will its impact be on employment and education, both short-term and long-term? How will AI reshape society, the economy, government, culture, and geopolitics?

A decade ago, developers built information-sharing software by writing a lot of custom code in a single code base, then adding layers of caching. Now we build information systems: interdependent software and services, data platforms, and event streams. Many of our software-to-systems initiatives fail, though, and when they do, we double down on traditional linear approaches. But linear thinking cannot resolve systems challenges. We need to shift to systems thinking.

This book walks you through the "need-to-know" aspects of artificial intelligence, including natural language processing, speech recognition, and the power of machine learning to show you how to make the most of this technology in a practical, tactical way. Case studies show how real-world companies are taking the next leap forward. Artificial intelligence and machine learning provide a data-driven basis for more robust and intensely-targeted marketing strategies - and companies that effectively utilize these latest tools will reap the benefit in the marketplace.

Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way statistical claims can be sensationalised, particularly in the media. In the age of big data, as data science becomes established as a discipline, a basic grasp of statistical literacy is more important than ever. In The Art of Statistics, David Spiegelhalter guides the listener through the essential principles we need in order to derive knowledge from data.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.

If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.

One of the greatest physicists of the twentieth century, Richard Feynman possessed an unquenchable thirst for adventure and an unparalleled ability to tell the stories of his life. "What Do You Care What Other People Think?" is Feynman's last literary legacy, prepared with his friend and fellow drummer, Ralph Leighton.

In today's technological society, with an unprecedented amount of information at our fingertips, learning plays a more central role than ever. In How We Learn, Stanislas Dehaene decodes its biological mechanisms, delving into the neuronal, synaptic and molecular processes taking place in the brain. He explains why youth is such a sensitive period, during which brain plasticity is maximal, but also assures us that our abilities continue into adulthood, and that we can enhance our learning and memory at any age.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

In this audiobook, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general listener, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context.

Artificial intelligence surrounds us. More and more of the systems and services you interact with every day are based on AI technology. Most AI is narrowly specific; that is, it can only do a single thing, in a single context. Human intelligence is different. We can solve a variety of tasks, including those we have not seen before. In Artificial General Intelligence, Julian Togelius explores technical approaches to developing more general artificial intelligence and asks what general AI would mean for human civilization.

In Understanding Software, Max Kanat-Alexander, Technical Lead for Code Health at Google, shows you how to bring simplicity back to computer programming. Max explains to you why programmers suck, and how to suck less as a programmer. There's just too much complex stuff in the world. Complex stuff can't be used, and it breaks too easily. Complexity is stupid. Simplicity is smart.

In the 1920s cotton buyer Earle Dickson worked for Johnson & Johnson and had a klutzy wife who often cut herself. The son of a doctor, Earle set out to create an easier way for her to bandage her injuries. Band-Aids were born, but Earle's bosses at the pharmaceutical giant weren't convinced, and it wasn't until the Boy Scouts of America tested Earle's prototype that this ubiquitous household staple was made available to the public.

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning.

Python is one of the easiest coding languages to master because it bases itself on the English language. Intuitive and simple, anyone can get started with programming in Python, almost overnight! It can even jumpstart your hobby or career in tech, taking you places you never thought you could go. And this is where this book comes into play… it’s your launchpad into the phenomenal world of Python programming.

The greatest tool is the hardest to use. Machine learning is the world's most important general-purpose technology—but it's notoriously difficult to launch. Outside Big Tech and a handful of other leading companies, machine learning initiatives routinely fail to deploy, never realizing value. What's missing? A specialized business practice suitable for wide adoption. In The AI Playbook, bestselling author Eric Siegel presents the gold-standard, six-step practice for ushering machine learning projects from conception to deployment.

The wonder of the natural world surrounds us - from the Amazon rain forest to the snowy peaks of Mount Everest to the green spaces in big cities. And as the threat of climate change grows, it’s more important than ever to show appreciation for our planet by taking action. The first audiobook in a middle-grade series for young environmental activists and nature lovers, The Wild World Handbook offers a road map for change and an invitation to explore the outdoors, alongside surprising facts and hands-on activities.