The Little Learner: A Straight Line to Deep Learning
| AUTHOR | Friedman, Daniel P.; Su, Qingqing; Mendhekar, Anurag et al. |
| PUBLISHER | MIT Press (02/21/2023) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
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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Product Format
Product Details
ISBN-13:
9780262546379
ISBN-10:
026254637X
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
More Product Details
Page Count:
440
Carton Quantity:
14
Product Dimensions:
6.93 x 1.26 x 8.90 inches
Weight:
1.50 pound(s)
Feature Codes:
Bibliography,
Index,
Price on Product
Country of Origin:
US
Subject Information
BISAC Categories
Computers | Data Science - Machine Learning
Computers | Artificial Intelligence - General
Computers | Programming - Algorithms
Dewey Decimal:
006.31
Library of Congress Control Number:
2022045341
Descriptions, Reviews, Etc.
publisher marketing
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
Show More
Your Price
$54.45