GenAI: Fast Data Synthetization with Distribution-free Hierarchical Bayesian Models
Deep learning models such as generative adversarial networks (GAN) require a lot of computing power, and are thus expensive. Also, they may not convergence. What if you could produce better data synthetizations, in a fraction of the time, with explainable AI and substantial cost savings? This is what Hierarchical Deep Resampling was designed for. It […]
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How to Fix a Failing Generative Adversarial Network
In this article, I explore different front-end strategies to improve a generative adversarial network (GAN) that leads to poor synthetization, in the context of tabular data generation. It is well known that tabular data is a lot more challenging than images, when using deep neural networks for synthetization purposes. An algorithm may work very well […]
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My Book on Generative AI Now on Amazon
Published by Elsevier, available in print in January 2024. You can pre-order it now, here. The PDF version is available on my e-store. The book is fully written. It is offered at a steep discount to participants in my Generative AI certification program, available here. This is the first technical book focusing on synthetic data and its […]
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