| The Little Learner: A Straight Line to Deep Learning (MIT Press) |
| Friday, 10 March 2023 | |||
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This book introduces deep learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of other books in the series such as The Little Schemer and The Little Typer, in this kindred text Daniel P. Friedman and Anurag Mendhekar explain the workings of deep neural networks by constructing them incrementally from first principles using little programs that build on one another. <ASIN:026254637X> 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. Author: Daniel P. Friedman and Anurag Mendhekar
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