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Generative AI with Python and TensorFlow 2

Generative AI with Python and TensorFlow 2

By : Joseph Babcock, Raghav Bali
4.4 (27)
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Generative AI with Python and TensorFlow 2

Generative AI with Python and TensorFlow 2

4.4 (27)
By: Joseph Babcock, Raghav Bali

Overview of this book

Machines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI? In this book, you’ll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. You’ll learn how to implement models yourself in TensorFlow and get to grips with the latest research on deep neural networks. There’s been an explosion in potential use cases for generative models. You’ll look at Open AI’s news generator, deepfakes, and training deep learning agents to navigate a simulated environment. Recreate the code that’s under the hood and uncover surprising links between text, image, and music generation.
Table of Contents (16 chapters)
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14
Other Books You May Enjoy
15
Index

Deepfakes with GANs

Manipulating videos and photographs to edit artifacts has been in practice for quite a long time. If you have seen movies like Forrest Gump or Fast and Furious 7, chances are you did not even notice that the scenes with John F. Kennedy or Paul Walker in their respective movies were fake and edited into the movies as required.

You may recall one particular scene from the movie Forrest Gump, where Gump meets John F. Kennedy. The scene was created using complex visual effects and archival footage to ensure high-quality results. Hollywood studios, spy agencies from across the world, and media outlets have been making use of editing tools such as Photoshop, After Effects, and complex custom visual effects/CGI (computer generated imagery) pipelines to come up with such compelling results. While the results have been more or less believable in most instances, it takes a huge amount of manual effort and time to edit each and every detail, such...

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