uclaacmai/Generative-Adversarial-Network-Tutorial
Tutorial on creating your own GAN in Tensorflow
This tutorial teaches you how to build a Generative Adversarial Network (GAN) from scratch. You'll learn to create a system where one part generates new, realistic data (like images) while another part evaluates its authenticity. This is for machine learning engineers or researchers interested in deep learning model architectures.
472 stars. No commits in the last 6 months.
Use this if you want to understand the foundational principles and implementation of GANs using TensorFlow for generating synthetic data.
Not ideal if you are looking for a pre-built application or a high-level library to use GANs without understanding their internal workings.
Stars
472
Forks
184
Language
Jupyter Notebook
License
—
Category
Last pushed
Oct 07, 2018
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/uclaacmai/Generative-Adversarial-Network-Tutorial"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
huggingface/pytorch-pretrained-BigGAN
🦋A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.
torchgan/torchgan
Research Framework for easy and efficient training of GANs based on Pytorch
metal3d/keras-video-generators
Keras generators to generate sequences from videos as input
GANs-in-Action/gans-in-action
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
junyanz/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch