Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings

This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. 神经网络模型的理论证明与基于Numpy的实现。

License

Notifications You must be signed in to change notification settings

yuanxiaosc/Theoretical-Proof-of-Neural-Network-Model-and-Implementation-Based-on-Numpy

Folders and files

NameName
Last commit message
Last commit date

Latest commit

History

3 Commits

Repository files navigation

Theoretical-Proof-of-Neural-Network-Model-and-Implementation-Based-on-Numpy

Talk is easy ,show me the proof and code.

This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. 神经网络模型的理论证明与基于Numpy的实现。

Installation

This repo was tested on Python 3.6

pip install numpy

Feedforward neural network 前馈神经网络模型图

Recurrent neural network 循环神经网络模型图

About

This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. 神经网络模型的理论证明与基于Numpy的实现。

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

AltStyle によって変換されたページ (->オリジナル) /