Neural Networks with JavaScript Succinctly

Download free course Neural Networks with JavaScript Succinctly, pdf file on 163 pages by James McCaffrey.

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.

Table of contents

Getting Started
Input and Output
Training
Overfitting
Regression
Binary Classification

Pages :	163
Size :	2.5 MB
Downloads:	133
Created:	2022-02-03
License:	For personal or educational use
Author(s):	James McCaffrey

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