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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

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

In this chapter, we will dive into the various applications of generative models. Before that, we will take a step back and examine how exactly generative models are different from other types of machine learning. The difference lies with the basic units of any machine learning algorithm: probability and the various ways we use mathematics to quantify the shape and distribution of data we encounter in the world.

In the rest of this chapter, we will cover:

Applications of AI
Discriminative and generative models
Implementing generative models
The rules of probability
Why use generative models?
Unique challenges of generative models

The rest of the chapter is locked

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Authors (2)

Joseph Babcock

See other products by Joseph Babcock

Raghav Bali

See other products by Raghav Bali

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