Artificial Intelligence Machine Learning

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.

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.

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.

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.

Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to apply time-tested software engineering skills and Lean product delivery practices to reduce toil and waste, shorten feedback loops, and improve your team's flow when building ML systems and products.

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.

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.

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 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.

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.

If you read (or listen to) nothing else on artificial intelligence and machine learning, listen to these ten articles. We've combed through hundreds of Harvard Business Review articles and selected the most important ones to help you understand the future direction of AI, bring your AI initiatives to scale, and use AI to transform your organization.

Machines That Think explores how artificial intelligence helps us understand human intelligence, machines that compose music and write stories - and asks if AI is really a threat. Sometime in the future, the intelligence of machines will exceed that of human brain power. So are we on the edge of an AI-pocalypse, with superintelligent devices superseding humanity, as predicted by Stephen Hawking? Or will this herald a kind of utopia, with machines doing a far better job at complex tasks than us?

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.

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 want to learn key AI concepts to get you quickly up to speed with all things AI, then pay attention...This audiobook covers everything from machine learning to robotics and the internet of things. By the time you finish listening, you will be aware of what artificial neural networks are, how gradient descent and back propagation work, and what deep learning is. You will also learn a comprehensive history of AI, from the first invention of automations in antiquity to the driver-less cars of today.

Unleash the power of Generative AI in less than 30 days. Turn tech curiosity into a practical skillset even if you're a beginner. Don't let your perception of what's difficult hold you back. This book is designed specifically with simplicity in mind, tailored for those who may be stepping into the world of AI for the first time. It is packed with interactive, up-to-date exercises and real-world applications, that will guide you every step of the way, ensuring that you stay connected to the most relevant and useful topics in AI.

From Oxford's leading AI researcher comes a fun and accessible tour through the history and future of one of the most cutting edge and misunderstood field in science: artificial intelligence.

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.

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.

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.