Learning Technology

The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX! Deep Learning with Python (Third Edition) puts the power of deep learning in your hands. This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python.

Artificial intelligence has changed how money is built, shifting the advantage toward those who move early. What once required years of effort can now be created through leverage instead of grind, making passive income accessible to anyone who understands the system. This 2-in-1 guide, offers a clear path to building income streams that grow beyond your time and effort. Start now and put yourself on the side of automated income that compounds forward.

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!

Everywhere we turn, a new device promises to transfigure our lives. But at what cost? In this urgent and revelatory excavation of our Information Age, leading technology thinker Adam Greenfield forces us to reconsider our relationship with the networked objects, services, and spaces that define us. It is time to re-evaluate the Silicon Valley consensus determining the future. We're told that innovations - from augmented - reality interfaces and virtual assistants to autonomous delivery drones and self-driving cars - will make life easier, more convenient, and more productive.

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.

Unlock the Secrets of AI Deep Learning and Neural Networks: Empower Your Future in Minutes a Day! Ready to dive into the world of artificial intelligence, but don’t know where to start? Whether you're a student, developer, or curious learner, this book takes you on a journey to master deep learning concepts, demystify neural networks, and transform your skills into real-world impact—all at your own pace.

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.

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.

Somewhere buried in all the systems that drive artificial intelligence, you'll find machine learning―the process that allows technology to build knowledge based on data and patterns. Machine Learning For Dummies is an excellent starting point for anyone who wants deeper insight into how all this learning actually happens. This book offers an overview of machine learning and its most important practical applications.

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 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.

Unravel the secrets of the AI revolution in just 7 days, even if you've never written a line of code! Do terms like "Machine Learning" or "Neural Networks" confuse you? Eager to understand AI but unsure where to start? You're not alone. Many believe mastering AI is only for tech experts. But here's the truth: Anyone can learn AI, and this guide shows you how!

To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting - and lucrative! - careers in some of today’s hottest programming fields about the technology.

Are you interested in learning about programming but don’t know where to start? Do you want to avoid the common pitfalls that self-taught programmers tend to often make? Do you want to clear your misconceptions about the process of programming? If you answered yes to any of these questions then this audiobook is for you.... 50 Things to Know About Learning Programming by Kirollos Hanna offers a look inside a learning programmer’s mind and experiences. Most books on programming tell you to learn the rules of programming without telling what to do with those rules.

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.

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 U.S. Department of Education (Department) is committed to supporting the use of technology to improve teaching and learning and to support innovation throughout educational systems. This report addresses the clear need for sharing knowledge and developing policies for “Artificial Intelligence,” a rapidly advancing class of foundational capabilities which are increasingly embedded in all types of educational technology systems and are also available to the public.

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.

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.