The Little Learner: A Straight Line to Deep Learning by Daniel P. Friedman (Engl

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"A gentle but detailed introduction to some of the algorithmic ideas behind machine learning"--

FORMATPaperback LANGUAGEEnglish CONDITIONBrand New Publisher Description

A highly accessible, step-by-step introduction to deep learning, written in an engaging, question-and-answer style.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 funIncremental approach constructs advanced concepts from first principlesPresents key ideas of machine learning using a small, manageable subset of the Scheme languageSuitable for anyone with knowledge of high school math and some programming experience

Author Biography

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. His career has spanned a range of technologies including distributed systems, image and video compression, and video distribution for VR.

Table of Contents

Foreword by Guy L. Steele Jr. xiForeword by Peter Norvig xiiiPreface xixTranscribing to Scheme xxiii0. Are You Schemish? 21. The Lines Sleep Tonight 182. The More We Learn, the Tenser We Become 30Interlude I. The More We Extend, the Less Tensor We Get 463. Running Down a Slippery Slope 564. Slip-slidin' Away 72Interlude II. Too Many Toys Make Us Hyperactive 925. Target Practice 98Interlude III. The Shape of Things to Come 1126. An Apple a Day 1167. The Crazy "ates" 1308. The Nearer Your Destination, the Slower You Become 144Interlude IV. Smooth Operator 1549. Be Adamant 162Interlude V. Extensio Magnifico! 17610. Doing the Neuron Dance 19411. In Love with the Shape of Relu 21212. Rock Around the Block 23613. An Eye for an Iris 250Interlude VI. How the Model Trains 270Interlude VII. Are Your Signals Crossed? 28214. It's Really Not That Convoluted 29815. ...But It Is Correlated! 320Epilogue. We've Only Just Begun 342Appendix A. Ghost in the Machine 350Appendix B. I Could Have Raced All Day 374Acknowledgments 399References 401Index 402

Details ISBN026254637X Author Anurag Mendhekar Short Title The Little Learner Language English Year 2023 ISBN-10 026254637X ISBN-13 9780262546379 Subtitle A Straight Line to Deep Learning Illustrator Qingqing Su Format Paperback Publication Date 2023-02-21 Publisher MIT Press Ltd Imprint MIT Press Country of Publication United States AU Release Date 2023-02-21 NZ Release Date 2023-02-21 US Release Date 2023-02-21 UK Release Date 2023-02-21 Illustrations 27 B&W ILLUS. Pages 436 DEWEY 006.31 Audience General We've got this

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