Książka Generative AI with Python and TensorFlow 2 Raghav Bali

Generative AI with Python and TensorFlow 2

Autor: Raghav Bali
Język: Angielski
Oprawa: Miękka
Dostępność: Dostępna u dostawcy
Wysyłamy za 9-15 dni
274.19
Fun and exciting projects to learn what artificial minds can create Key Features:Code examples are i...

Informacje o książce

Autor
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2021
strony
488
EAN
9781800200883
ISBN
1800200889
Enbook ID
36184609
Waga
902
Wymiary
191 x 235 x 26

Pełny opis

Fun and exciting projects to learn what artificial minds can create 


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


Book Description:

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.


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


Who this book is for:

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. 

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