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Neural Networks with JavaScript Succinctly

by James McCaffrey

Neural Networks with JavaScript Succinctly

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Book Description

James McCaffrey leads you through the fundamental concepts of neural networks, including their architecture, input-output, tanh and softmax activation, back-propagation, error and accuracy, normalization and encoding, and model interpretation. Although most concepts are relatively simple, there are many of them, and they interact with each other in unobvious ways, which is a major challenge of neural networks. But you can learn all important neural network concepts by running and examining the code in Neural Networks with JavaScript Succinctly, with complete example programs for the three major types of neural network problems.

This open book is licensed strictly for personal or educational use. You can download Neural Networks with JavaScript Succinctly ebook for free in PDF format (2.5 MB).

Table of Contents

Chapter 1
Getting Started
Chapter 2
Input and Output
Chapter 3
Training
Chapter 4
Overfitting
Chapter 5
Regression
Chapter 6
Binary Classification

Book Details

Title
Neural Networks with JavaScript Succinctly
Subject
Computer Science
Publisher
Syncfusion
Published
2019
Pages
163
Edition
1
Language
English
PDF Size
2.5 MB
License
For personal or educational use

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