The Little Learner: A Straight Line to Deep Learning by Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig, Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig

Download amazon ebooks ipad The Little Learner: A Straight Line to Deep Learning by Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig, Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig 9780262546379

Download The Little Learner: A Straight Line to Deep Learning PDF

The Little Learner: A Straight Line to Deep Learning
Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig, Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig
Page: 440
Format: pdf, ePub, mobi, fb2
ISBN: 9780262546379
Publisher: MIT Press

Download The Little Learner: A Straight Line to Deep Learning

Download amazon ebooks ipad The Little Learner: A Straight Line to Deep Learning by Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig, Daniel P. Friedman, Anurag Mendhekar, Qingqing Su, Guy L. Steele Jr., Peter Norvig 9780262546379

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

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The Little Learner: A Straight Line to Deep Learning - Amazon
The Little Learner: A Straight Line to Deep Learning | Friedman, Daniel P., Mendhekar, Anurag, Su, Qingqing, Steele Jr., Guy L., Norvig, Peter | ISBN:
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Coming Soon - Artificial Intelligence / Computer Science
The Little Learner: A Straight Line to Deep Learning. by Daniel P. Friedman, Anurag Mendhekar , et al. | Sold by: Amazon Media EU S.à
DANIEL FRIEDMAN auf LinkedIn: #deeplearning
Excited and proud to announce the release date of my next book (with co-author Anurag M.) The Little Learner: A Straight Line to Deep Learning,
Announcing The Little Learner: A Straight Line to Deep Learning
"The Little Learner" covers all the concepts necessary to develop an intuitive understanding of the workings of deep neural networks: tensors, extended

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