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.

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.

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.

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.

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.

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.

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.

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.

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.

Artificial intelligence is smarter than humans. It can process information at lightning speed and remain focused on specific tasks without distraction. AI can see into the future, predicting outcomes and even use sensors to see around physical and virtual corners. So why does Intelligence frequently get it so wrong? The answer is us. Humans design the algorithms that define the way that AI works and the processed information reflects an imperfect world.

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.

This helpful, plain-English guide provides need-to-know information on how to choose the right system, assure patients of the security of their records, and implement an EHR in such a way that it causes minimal disruption to the daily demands of a hospital or clinic.

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.

Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML 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.

Instructional design offers powerful ways to build training and teach new skills, but its methods run DEEP. Finding a clear, easy-to-follow path can be frazzling. Where do you even start? Whether you’re a new instructional designer, looking to transition from another job, or tasked with training for your organization, this book will help get you rolling! We’ll dig into examples and spin tips, tactics, and research-backed learning principles into a professional workflow.

Developed by experienced professors and professionally narrated for easy listening, this course is a valuable tool when preparing for your ITIL 4 foundation exam. The audio is focused and high-yield, covering the most important topics you need to know to succeed on The Information Technology Infrastructure Library (ITIL) Level 4 foundation exam. The material is accurate, up-to-date, and broken down into bite-sized chapters. There are key takeaways following each chapter to drive home key points and quizzes to review commonly tested questions.

This groundbreaking book is your ultimate guide to understanding and leveraging the power of artificial intelligence. Whether you're a curious beginner, a tech enthusiast, or an entrepreneur ready to revolutionize your business, this guide provides you with everything you need to navigate the AI-driven future.

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.