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Steele Jr. and Peter Norvig * $55.00 Paperback 440 pp., 7 x 9 in, 27 b&w illus. * Paperback * 9780262546379 * Published: February 21, 2023 * Publisher: The MIT Press $55.00 * Penguin Random House * Amazon * Barnes and Noble * Bookshop.org * Indiebound * Indigo * Books a Million Other Retailers: * Amazon.co.uk * Blackwells * Bookshop.org * Foyles * Hive * Waterstones * Penguin Random House * Amazon * Barnes and Noble * Bookshop.org * Indiebound * Indigo * Books a Million * Request exam/desk copy * Request permissions * Description * Author(s) * Praise * Resources A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style. The Little Learner introduces deep learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The Little Typer, this kindred text explains the workings of deep neural networks by constructing them incrementally from first principles using little programs that build on one another. Starting from scratch, the reader is led through a complete implementation of a substantial application: a recognizer for noisy Morse code signals. Example-driven and highly accessible, The Little Learner covers all of the concepts necessary to develop an intuitive understanding of the workings of deep neural networks, including tensors, extended operators, gradient descent algorithms, artificial neurons, dense networks, convolutional networks, residual networks, and automatic differentiation. * Conversational style, illustrations, and question-and-answer format make deep learning accessible and fun * Incremental approach constructs advanced concepts from first principles * Presents key ideas of machine learning using a small, manageable subset of the Scheme language * Suitable for anyone with knowledge of high school math and some programming experience Daniel P. Friedman is Professor of Computer Science in the School of Informatics, Computing, and Engineering at Indiana University and is the author of many books published by the MIT Press, including The Little Schemer and The Seasoned Schemer (with Matthias Felleisen); The Little Prover (with Carl Eastlund); and The Reasoned Schemer (with William E. Byrd, Oleg Kiselyov, and Jason Hemann). Anurag Mendhekar is Cofounder and President of Paper Culture, where he focuses on developing artificial intelligence for creativity, and an entrepreneur. He started his career at Xerox's Palo Alto Research Center (PARC), where he was one of the inventors of aspect-oriented programming. "Friedman's 'Little Books' are famous for teaching important topics in bite-sized, easily-digestible pieces. Now Friedman and Mendhekar have turned their attention to machine learning, and they have succeeded masterfully." Mitchell Wand, professor emeritus and part-time lecturer of computer science in the Khoury College of Computer Sciences, Northeastern University; coauthor of Essentials of Programming Languages Table of Contents Related Books Machine Decision Is Not Final Artificial Intelligence Living with Robots Architectural Intelligence Models of a Man Neurorobotics Microprediction Awkward Intelligence Working with AI Once Upon an Algorithm logo * Column 1 + Books + Journals + The MIT Press Reader + Podcasts + Imprints * Column 2 + The MIT Press o About o Bookstore o Catalogs o Conferences o Press Editorial Board o Jobs o Internships o Press Management Board o News o Staff o Code of Conduct o Give * Column 3 + Site Help o Accessibility o FAQ o Our eBooks o Privacy Policy o Terms of Use * Column 4 + Resources o Current Authors o Prospective Authors o Booksellers o Instructors o Rights and Permissions o Media Inquiries o MIT Discounts * Column 5 + Digital o CogNet o Digital Partners and Products o Knowledge Futures Group o MIT Press Direct * US One Broadway 12th Floor Cambridge, MA 02142 * UK Unit 57710 PO Box 6945 London W1A 6US UK * Contact Connect (c) 2023 MIT Press. 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