The Science of Deep Learning - Hardcover

Drori, Iddo

Hardcover

ISBN 10: 1108835082 ISBN 13: 9781108835084

Publisher: Cambridge University Press, 2022

Synopsis

The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies. prepared them for careers in deep learning, machine learning. artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state of the art topics such as Transformers, graph neural networks, variational autoencoders. deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization. best practices in scientific writing and reviewing. The text presents an up to date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.

About this title

About the Author

Iddo Drori is an Associate Professor of Computer Science, faculty of practice at Boston University, visiting at MIT, and adjunct at Columbia University. He was a visiting associate professor at Cornell University in operations research and information engineering, and a research scientist and adjunct professor at NYU Center for Data Science, Courant Institute, and NYU Tandon. He holds a Ph.D. in computer science and was a postdoctoral research fellow at Stanford University in Statistics. He also holds an MBA in organizational behavior and entrepreneurship and has a decade of industry research and leadership experience. His main research is in machine learning, AI, and computer vision, with 70 publications and over 5,200 citations, and has taught over 35 courses in computer science. He has won multiple competitions in computer vision conferences and received multiple best paper awards in machine learning conferences.

Edition details

• Publisher: Cambridge University Press
• Publication date: 2022
• Language: English
• ISBN 10: 1108835082
• ISBN 13: 9781108835084
• Binding: Hardcover
• Number of pages: 360