Showing results for "Learning Science and the Science of Learning" in Computers & Technology

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.

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.

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.

As data floods into your company, you need to put it to work right away—and SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps developers get up to speed with SQL fundamentals for writing database applications, performing administrative tasks, and generating reports. You'll find new chapters on SQL and big data, analytic functions, and working with very large databases.

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.

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.

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. The book addresses real-life problems faced by practitioners on a daily basis and explains scientifically sound solutions using math, supported by code and examples.

Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models.

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.

Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently bingeable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Artificial intelligence (AI) and performance expert Josh Cavalier shares his in-depth knowledge and skills to help L&D professionals master learning experience design by using generative AI in their employee learning and development efforts. More than just a technical manual on generative AI or a collection of best prompt practices, this book explores how AI is reshaping jobs, skill development, and human performance. Cavalier provides his Learning and Development AI Ecosystem framework as a practical road map for integrating AI into your day-to-day work and your organization.

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.

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 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.

In a world driven by technological advancements, the potential of Artificial Intelligence (AI) is limitless. However, understanding the complexities of AI and harnessing its transformative power can be a daunting task. This audiobook is the solution you've been searching for. This comprehensive guide dives deep into the world of AI, providing you with the knowledge, tools, and techniques to master the art of AI and Generative AI.

Unlock the Power of Generative AI: Master Creativity, Deep Learning, and Advanced AI in One Essential Collection! Are you ready to revolutionize your creativity, career, and understanding of artificial intelligence? Whether you're an absolute beginner or looking to sharpen your AI expertise, this book collection takes you on a transformative journey through the world of Generative AI, Deep Learning, and Neural Networks. Discover How AI Can Save You Time, Enhance Creativity, and Propel Your Career Forward!

The definitive exploration of one of the most daring and consequential theories of our time, completely revised and updated to reflect the rapid advances in artificial intelligence and virtual reality Are we living in a simulation? MIT computer scientist Rizwan Virk draws from research and...

In AI for Good: Applications in Sustainability, Humanitarian Action, and Health, a team of veteran Microsoft AI researchers delivers an insightful and fascinating discussion of how one of the world's most recognizable software companies is tackling intractable social problems with the power of artificial intelligence (AI). In the book, you'll see real in-the-field examples of researchers using AI with replicable methods and reusable AI code to inspire your own uses.

In Part I, this book develops the Cognitive Amplifier Loop, which allows humans to use AI to build on their cognitive and emotional strengths and manage their limitations. Kosslyn discusses ways to employ this loop to offload tasks to AI and to utilize it to train us effectively and efficiently, as well as how to use it to both learn and engage in critical thinking and creative problem-solving—and manage cognitive and emotional constraints. Part II establishes how to draw on the Cognitive Amplifier Loop to help us improve our human relationships.

In this groundbreaking and practical guide, teachers will discover how to harness and manage AI as a powerful teaching tool. Jose Antonio Bowen and C. Edward Watson present emerging and powerful research on the seismic changes AI is already creating in schools and the workplace, providing invaluable insights into what AI can accomplish in the classroom and beyond.