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.
publication date
2021-04-30
what you will learn
Export the code from GitHub into Google Colab to see how everything works for yourself
Compose music using LSTM models, simple GANs, and MuseGAN
Create deepfakes using facial landmarks, autoencoders, and pix2pix GAN
Learn how attention and transformers have changed NLP
Build several text generation pipelines based on LSTMs, BERT, and GPT-2
Implement paired and unpaired style transfer with networks like StyleGAN
Discover emerging applications of generative AI like folding proteins and creating videos from images
key features
Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along * Look inside the most famous deep generative models, from GPT to MuseGAN * Learn to build and adapt your own models in TensorFlow 2.x * Explore exciting, cutting-edge use cases for deep generative AI
approach
This book takes a hands-on approach, with the material on each class of model containing code examples, implementation details, and explanations that give you a deeper appreciation of how and why these models work. It also emphasizes references to the latest research so you can expand your knowledge beyond this volume.
audience
This is a book for Python programmers who are keen to create and have some fun using generative models. To make the most out of this book, you should have a basic familiarity with math and statistics for machine learning.
short description
Packed with intriguing real-world projects as well as theory, Generative AI with Python and TensorFlow 2 enables you to leverage artificial intelligence creatively and generate human-like data in the form of speech, text, images, and music.
subtitle
Create images, text, and music with VAEs, GANs, LSTMs, Transformer models
keywords
PyTorch, TensorFlow Keras, TensorFlow book, TensorFlow for deep learning, real-world AI, practical AI, hands-on AI, GAN, GANs
Product ISBN
9781800200883
