zurutech/gans-from-theory-to-production
Material for the tutorial: "Deep Diving into GANs: from theory to production"
This tutorial guides machine learning practitioners through creating realistic synthetic images and other data using Generative Adversarial Networks (GANs). It takes theoretical concepts and translates them into practical TensorFlow implementations, culminating in deployment on Google Cloud Functions. Data scientists, ML engineers, or researchers looking to build and deploy image generation models will find this useful.
210 stars. No commits in the last 6 months.
Use this if you need to learn how to develop, implement, and deploy GAN models to generate new data or images, moving from fundamental concepts to production-ready solutions.
Not ideal if you are looking for a pre-built solution or a high-level API for immediate image generation without understanding the underlying mechanics or deployment.
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210
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Jupyter Notebook
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MPL-2.0
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Last pushed
Mar 24, 2023
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