hklchung/GAN-GenerativeAdversarialNetwork

Beginner's Guide to building GAN from scratch with Tensorflow and Keras

27
/ 100
Experimental

This project offers a practical, hands-on guide to building Generative Adversarial Networks (GANs) using Keras and TensorFlow. It helps machine learning enthusiasts learn how to generate realistic images, perform conditional image generation, and translate images without paired examples. You'll input publicly available image datasets and, through clear code examples, learn to output new, synthetically generated images.

No commits in the last 6 months.

Use this if you are a machine learning beginner or enthusiast eager to understand and implement various GAN architectures for image generation tasks with working, reproducible code.

Not ideal if you are looking for an advanced, production-ready GAN framework or a deep theoretical dive without practical implementation.

image generation machine learning education deep learning practice synthetic data creation computer vision learning
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 13 / 25

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Stars

16

Forks

3

Language

Python

License

—

Category

gan-architectures-implementations

Last pushed

Mar 25, 2023

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Gan Architectures Implementations · 3 tools

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