<p><strong>Fun and exciting projects to learn what artificial minds can create </strong></p><p><br></p><p><strong>Key Features: </strong></p><ul><li>Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along</li><li>Look inside the most famous deep generative models, from GPT to MuseGAN</li><li>Learn to build and adapt your own models in TensorFlow 2.x</li><li>Explore exciting, cutting-edge use cases for deep generative AI</li></ul><p><br></p><p><strong>Book Description: </strong></p><p>Machines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI?</p><p><br></p><p>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.</p><p><br></p><p>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.</p><p><br></p><p>Recreate the code that's under the hood and uncover surprising links between text, image, and music generation.</p><p><br></p><p><strong>What You Will Learn: </strong></p><ul><li>Export the code from GitHub into Google Colab to see how everything works for yourself</li><li>Compose music using LSTM models, simple GANs,