https://github.com/zombietdv/cnn_and_beta-vae-

CNN and Beta-VAE implementation. Only Numpy as the main library.
https://github.com/zombietdv/cnn_and_beta-vae-

automatic-differentiation backpropagation-algorithm beta-vae cnn deep-learning numpy optimization-algorithms

Last synced: about 1 month ago
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CNN and Beta-VAE implementation. Only Numpy as the main library.

• Host: GitHub
• URL: https://github.com/zombietdv/cnn_and_beta-vae-
• Owner: zombieTDV
• Created: 2024-11-07T12:41:51.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-07T13:12:53.000Z (about 2 months ago)
• Last Synced: 2024-11-28T04:07:35.975Z (about 1 month ago)
• Topics: automatic-differentiation, backpropagation-algorithm, beta-vae, cnn, deep-learning, numpy, optimization-algorithms
• Language: Python
• Homepage:
• Size: 113 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Overview:    

-My newest version on AvK( my library for Deep learning, you can think of it like a meme copy of Tensorflow or Pytorch ).   

-This time, I added tons more things compared to the old version in HM_GPT.  

-With roughly 2500 lines of code, I used it for Convolutional Neural Networks and Beta-Variational-Autoencoder.   

-I added a lot of comments, documents, and overviews of every file.   

How to use it?    

-Run the Beta_VAE.py file for Beta-Variational-Autoencoder.   

-Run the CNN.py file for Convolutional Neural Network.  

-But the main application is actually the SUPER_AVK file, it has all my newest implementations for a Deep learning library.   

-You should only use it for learning cause it may not be efficient for real-life projects.