A visual proof that neural nets can compute any function

https://neuralnetworksanddeeplearning.com/chap4.html

A visual proof that neural nets can compute any function

This webpage is part of the online book "Neural Networks and Deep Learning" and specifically focuses on chapter 4. The chapter discusses the concept of gradient descent, which is an optimization algorithm commonly used in training neural networks. It explains how gradient descent works mathematically and provides intuitive explanations. The webpage also provides interactive visualizations to help readers understand the concept better. It covers topics like learning rate, local minima, and stochastic gradient descent. Overall, this chapter serves as a comprehensive guide to understanding and implementing gradient descent in the context of neural networks.

by Nielsen, Michael A. · 26 min · 9.21.2014

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https://neuralnetworksanddeeplearning.com/chap4.html

Summary

This webpage is part of the online book "Neural Networks and Deep Learning" and specifically focuses on chapter 4. The chapter discusses the concept of gradient descent, which is an optimization algorithm commonly used in training neural networks. It explains how gradient descent works mathematically and provides intuitive explanations. The webpage also provides interactive visualizations to help readers understand the concept better. It covers topics like learning rate, local minima, and stochastic gradient descent. Overall, this chapter serves as a comprehensive guide to understanding and implementing gradient descent in the context of neural networks.
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