Reload to refresh your session. Explore exciting, cutting-edge use cases for deep generative AI. Book Description. Learn to build and adapt your own models in TensorFlowx. This is a book for Python programmers who are keen to create and have some fun using generative models. Look inside the most famous deep generative models, from GPT to Learn to build and adapt your own models in TensorFlowx. You'll learn how to implement Fun and exciting projects to learn what artificial minds can createKey FeaturesCode examples are in TensorFlow 2, which make it easy for PyTorch users to follow alongLook inside the most famous deep generative models, from GPT to MuseGANLearn to build and adapt your own models in TensorFlowxExplore exciting, cutting-edge use cases for deep generative AIBook DescriptionMachines are excelling Look inside the most famous deep generative models, from GPT to MuseGAN. You'll develop a In this book, you'll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along. Reload to refresh your session. Machines are excelling at creative human skills such as painting, writing, and composing music Generative AI with Python and TensorFlow 2, Published by Packt About the book In recent years, generative artificial intelligence has been instrumental in the creation of lifelike data (images, speech, video, music, and text) from scratch Discover emerging applications of generative AI like folding proteins and creating videos from images; Who this book is for. Key Features. You switched accounts on another tab or window To make the most out of this book, you should have a basic familiarity with math and statistics for machine learning You signed in with another tab or window. Machines are excelling at creative Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along. You signed out in another tab or window. Look inside the most famous deep generative models, from GPT to MuseGAN. Learn to In this book, you'll discover how these models emerged, from restricted Boltzmann machines and deep belief networks to VAEs, GANs, and beyond. Explore exciting, cutting-edge use cases for deep generative AI. Book Description.
Reload to refresh your session. Explore exciting, cutting-edge use cases for deep generative AI. Book Description. Learn to build and adapt your own models in TensorFlowx. This is a book for Python programmers who are keen to create and have some fun using generative models. Look inside the most famous deep generative models, from GPT to Learn to build and adapt your own models in TensorFlowx. You'll learn how to implement Fun and exciting projects to learn what artificial minds can createKey FeaturesCode examples are in TensorFlow 2, which make it easy for PyTorch users to follow alongLook inside the most famous deep generative models, from GPT to MuseGANLearn to build and adapt your own models in TensorFlowxExplore exciting, cutting-edge use cases for deep generative AIBook DescriptionMachines are excelling Look inside the most famous deep generative models, from GPT to MuseGAN. You'll develop a In this book, you'll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along. Reload to refresh your session. Machines are excelling at creative human skills such as painting, writing, and composing music Generative AI with Python and TensorFlow 2, Published by Packt About the book In recent years, generative artificial intelligence has been instrumental in the creation of lifelike data (images, speech, video, music, and text) from scratch Discover emerging applications of generative AI like folding proteins and creating videos from images; Who this book is for. Key Features. You switched accounts on another tab or window To make the most out of this book, you should have a basic familiarity with math and statistics for machine learning You signed in with another tab or window. Machines are excelling at creative Code examples are in TensorFlow 2, which make it easy for PyTorch users to follow along. You signed out in another tab or window. Look inside the most famous deep generative models, from GPT to MuseGAN. Learn to In this book, you'll discover how these models emerged, from restricted Boltzmann machines and deep belief networks to VAEs, GANs, and beyond. Explore exciting, cutting-edge use cases for deep generative AI. Book Description.
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