Welcome to Autoencoder’s documentation!¶
This is a neural networks from scratch library which has been created for the course “Numerical methods of algorithmic systems and neural networks” which has been taught in the summer semester 2020 at the Leibniz Universität Hannover by Prof. Thomas Wick.
Table of Contents:
- Getting started: Overview & Installation
- Basics of Deep Learning
- Multi-Layer Perceptron: Classification of handwritten digits (MNIST)
- Denoising Autoencoder: Removing noise from the MNIST dataset
- VAE: Creating new handwritten numbers based on MNIST
- Generative Adversarial Networks: Creating new numbers
- License
- Help