Description: Little Learner : A Straight Line to Deep Learning, Paperback by Friedman, Daniel P.; Mendhekar, Anurag; Su, Qingqing (ILT); Steele, Guy L. (FRW); Norvig, Peter (AFT), ISBN 026254637X, ISBN-13 9780262546379, Like New Used, Free shipping in the US 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
Price: 60.08 USD
Location: Jessup, Maryland
End Time: 2024-12-03T19:05:35.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 14 Days
Refund will be given as: Money Back
Return policy details:
Book Title: Little Learner : A Straight Line to Deep Learning
Number of Pages: 440 Pages
Publication Name: Little Learner : a Straight Line to Deep Learning
Language: English
Publisher: MIT Press
Item Height: 1 in
Publication Year: 2023
Subject: Programming / Algorithms, Intelligence (Ai) & Semantics, General
Type: Textbook
Item Weight: 29.2 Oz
Subject Area: Computers, Science
Item Length: 9 in
Author: Anurag Mendhekar, Daniel P. Friedman
Item Width: 7 in
Format: Uk-Trade Paper
