hklchung/GAN-GenerativeAdversarialNetwork
Beginner's Guide to building GAN from scratch with Tensorflow and Keras
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.
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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.
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Python
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Last pushed
Mar 25, 2023
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