Metadata-Version: 2.1
Name: manim-ml
Version: 0.0.2
Summary: Machine Learning Animations in python using Manim
Home-page: https://github.com/helblazer811/ManimMachineLearning
Author: Alec Helbling
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/helblazer811/ManimMachineLearning/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.md

# Manim Machine Learning
<a href="https://github.com/helblazer811/ManimMachineLearning">
    <img src="examples/ManimMLLogo.gif">
</a>

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Manim Machine Learning is a project focused on providing animations and visualizations of common machine learning concepts with the [Manim Community Library](https://www.manim.community/). We want this project to be a compilation of primitive visualizations that can be easily combined to create videos about complex machine learning concepts. Additionally, we want to provide a set of abstractions which allow users to focus on explanations instead of software engineering.

## Table of Contents

1. [Getting Started](#getting-started)
2. [Examples](#examples)

## Getting Started 
First you will want to [install manim](https://docs.manim.community/en/stable/installation.html). Then you can run the following to generate the example videos. 

`manim -pqh src/vae.py VAEScene`

## Examples

Checkout the ```examples``` directory for some example videos with source code. 

### Variational Autoencoders

This is a visualization of a Variational Autoencoder. 

<img src="examples/VAEScene.gif" width="600">

### VAE Disentanglement 

This is a visualization of disentanglement with a Variational Autoencoder

<img src="examples/DisentanglementScene.gif" width="600">

### Neural Networks

This is a visualization of a Neural Network. 

<img src="examples/TestNeuralNetworkScene.gif" width="600">


