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Generative AI with Python and TensorFlow 2

You're reading from Generative AI with Python and TensorFlow 2

Product type Book

Published in Apr 2021

Publisher Packt

ISBN-13 9781800200883

Pages 488 pages

Edition 1st Edition

Languages

Concepts

Artificial Intelligence

Authors (2):

Joseph Babcock

Raghav Bali

View More author details

Table of Contents (16) Chapters

Preface

1. An Introduction to Generative AI: "Drawing" Data from Models

2. Setting Up a TensorFlow Lab

3. Building Blocks of Deep Neural Networks

4. Teaching Networks to Generate Digits

5. Painting Pictures with Neural Networks Using VAEs

6. Image Generation with GANs

7. Style Transfer with GANs

8. Deepfakes with GANs

9. The Rise of Methods for Text Generation

10. NLP 2.0: Using Transformers to Generate Text

11. Composing Music with Generative Models

12. Play Video Games with Generative AI: GAIL

13. Emerging Applications in Generative AI

14. Other Books You May Enjoy

15. Index

Summary

In this chapter, we examined a number of emerging applications of generative models. One is in the field of biotechnology, where they can be used to create large collections of new potential drug structures. Also in the biotechnology field, generative models are used to create potential protein folding structures that can be used for computational drug discovery.

We explored how generative models can be used to solve mathematical problems, in particular PDEs, by mapping a set of boundary conditions of a fluid dynamics equation to a solution grid. We also examined a challenging problem of generating videos from a limited set of input images, and finally generating complex textual descriptions (components and sequences of instructions) from images of food to create recipes.

Well done for reaching the end of the book. As a final summary, let's recap everything we've learned:

Chapter 1, An Introduction to Generative AI: "Drawing" Data from...

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Authors (2)

Joseph Babcock

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Raghav Bali

See other products by Raghav Bali

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