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https://i126.fastpic.org/big/2026/0104/33/af31d5deef97c8d00433b1dcc720d833.avif
English | 2026 | ISBN: B0FDVZWYRM | 542 pages | true epub PDF | 24 MB
Leverage Generative AI within the R programming environment and prepare for future directions and how new innovations can be applied in the R ecosystem. This pioneering book is designed to bridge the gap between the advanced realms of Generative AI and the practical, statistical computing power of R.
You'll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. You'll then dive into the practicalities of implementing generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) in R. See how R, most known for its statistical analysis, can also be used for creative synthetic data, improving model robustness, and generating innovative insights from data.

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