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.

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.

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.

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.

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 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 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.

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.

Need networking know-how, but don't know where to turn? Run-don't walk-to the no-nonsense networking guidance offered in this friendly guide! Whether you're a networking administrator or an everyday computer user looking to set up a network in your home or office, Networking for Dummies, seamlessly gets you connected with the basics and gives you the knowledge to work out whatever kinks may come your way-in no time.

Becoming a solutions architect requires a hands-on approach, and this edition of the Solutions Architect's Handbook brings exactly that. This audiobook will teach you how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. It will also help you build effective product strategies for your business and implement them from start to finish.

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.

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.

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.

Step into the future of education with Dr. Samuel Li’s groundbreaking exploration of how Generative AI, immersive technologies, and metaverse classrooms are reshaping learning for the next generation. Smart Education is part of the acclaimed Building Digital Twin Metaverse Cities book series, which provides insights into how emerging technologies are revolutionizing every aspect of our lives.

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.

This study guide follows the syllabus for the Microsoft AI Foundations exam (AI-900). More importantly, this audiobook will help you gain the foundational knowledge needed to become an AI practitioner. You do not need a mathematical or programming background to understand the concepts in this audiobook or to pass the AI-900 exam. This study guide does not contain any material that compromises the integrity of any Microsoft exam. All materials, including practice questions, were developed using the syllabus for the exam and thorough research of published articles.

Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success.

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.

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.