Learning Technology

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.

The author of this book has crafted an accessible introduction that demystifies machine learning without sacrificing accuracy or depth. By focusing on intuitive explanations, practical examples, and real-world applications, this guide bridges the gap between complex technical concepts and practical understanding. Whether you're a student considering a career in technology, a professional looking to understand how AI might impact your industry, or simply a curious individual wanting to understand the algorithms that increasingly shape our world, this book provides the foundation you need.

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements. Author Chip Huyen, cofounder of Claypot AI, considers each design decision in the context of how it can help your system as a whole achieve its objectives.

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.

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.

Drs. Barbara Oakley and Terrence Sejnowski's popular Online course Learning How to Learn, has enrolled more than 1.8 million students. In this much needed follow-up to A Mind for Numbers, the authors teach kids and teens how to learn effectively at a time when they most need these skills. Learning How to Learn teaches them about the importance of both focused concentration and letting their minds wander, how the brain makes connections between different pieces of information, why procrastination is the enemy of problem solving, and much more.

In today's fast-paced world, more and more organizations require rapid application development with reduced development costs and increased productivity. This practical guide shows application developers how to use Power Apps, Microsoft's low-code, no-code application framework that helps developers make apps faster, modernize business processes, and solve tough challenges. Author Arpit Shrivastava provides a comprehensive overview of designing and building cost-effective applications with Microsoft Power Apps.

(ISC)2 Certified Information Systems Security Professional (CISSP) Official Study Guide, 9th Edition has been completely updated based on the latest 2021 CISSP Exam Outline. This bestselling Sybex study guide covers 100% of the exam objectives. You'll prepare for the exam smarter and faster with Sybex thanks to expert content, knowledge from our real-world experience, advice on mastering this adaptive exam, access to the Sybex online interactive learning environment, and much more. Reinforce what you've learned with key topic exam essentials and chapter review questions.

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 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 initiatives, aka predictive AI projects, from conception to deployment.

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.

In Wiley's Certified Information Security Manager (CISM) Study Guide, you'll get the information you need to succeed on the demanding CISM exam. You'll also develop the IT security skills and confidence you need to prove yourself where it really counts: on the job. Chapters are organized intuitively and by exam objective so you can easily keep track of what you've covered and what you still need to study. You'll also get access to a pre-assessment, so you can find out where you stand before you take your studies further.

This audiobook is masterfully read by the author, Mo Gawdat. One of The Sunday Times' Business Books of the Year Technology is putting our humanity at risk to an unprecedented degree. This book is not for engineers who write the code or the policy makers who claim they can regulate it. This is a...

To most of us, it seems like recent developments in artificial intelligence emerged out of nowhere to pose unprecedented threats to humankind. But to Dr. Joy Buolamwini, who has been at the forefront of AI research, this moment has been a long time in the making.

We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.

You don't have to be a computer scientist to have discerning conversations about artificial intelligence and technology. We all wonder where we're headed. Even now, technological innovations and machine learning have a daily impact on our lives, and many of us see good reasons to dread the future. Are we doomed to the surveillance society imagined in George Orwell's 1984? Mathematician and philosopher John Lennox believes that there are credible responses to the daunting questions that AI poses.

30 Days to a More Powerful Vocabulary quickly became a bestseller in its category back in 2015. Now, in this updated and revised edition—which now contains the 700 most important words you need to master—you'll quickly learn why this title has been such a positive impact in the personal and professional lives of tens of thousands in the English-speaking world.

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.

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

More than half a century ago, the naturalist Farley Mowat accepted an assignment to investigate why wolves were killing Arctic caribou. Mowat’s account of the summer he lived in the frozen tundra alone – studying the wolf population and developing a deep affection for these wild creatures (who were no threat to caribou or man) – is today celebrated as a classic of nature writing, at once a tale of remarkable adventure and an indelible record of the myths and magic of wolves.