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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.

Dr. Catherine Kleier invites us to open our eyes to the phenomenal world of plant life and to the process she calls “Natura Revelata”, the joy of celebrating and learning from the secrets of nature. As Dr. Kleier shares her knowledge with contagious excitement for her subject, she emphasizes the middle ground: Instead of focusing on cell microbiology or the study of ecosystems and habitats, she stresses the basic biology, function, and the amazing adaptations of the plants we see all around us.

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.