{"product_id":"learn-generative-ai-with-pytorch-9781633436466","title":"Learn Generative AI with Pytorch","description":"\u003cb\u003eLearn how generative AI works by building your very own models that can write coherent text, create realistic images, and even make lifelike music.\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e\u003ci\u003eLearn Generative AI with PyTorch\u003c\/i\u003e teaches the underlying mechanics of generative AI by building working AI models from scratch. Throughout, you'll use the intuitive PyTorch framework that's instantly familiar to anyone who's worked with Python data tools. Along the way, you'll master the fundamentals of General Adversarial Networks (GANs), Transformers, Large Language Models (LLMs), variational autoencoders, diffusion models, LangChain, and more! \u003cp\u003e\u003c\/p\u003eIn \u003ci\u003eLearn Generative AI with PyTorch\u003c\/i\u003e you'll build these amazing models: \u003cp\u003e\u003c\/p\u003e- A simple English-to-French translator\u003cbr\u003e - A text-generating model as powerful as GPT-2\u003cbr\u003e - A diffusion model that produces realistic flower images\u003cbr\u003e - Music generators using GANs and Transformers\u003cbr\u003e - An image style transfer model\u003cbr\u003e - A zero-shot know-it-all agent \u003cp\u003e\u003c\/p\u003e The generative AI projects you create use the same underlying techniques and technologies as full-scale models like GPT-4 and Stable Diffusion. You don't need to be a machine learning expert--you can get started with just some basic Python programming skills. \u003cp\u003e\u003c\/p\u003e Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the technology\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e Transformers, Generative Adversarial Networks (GANs), diffusion models, LLMs, and other powerful deep learning patterns have radically changed the way we manipulate text, images, and sound. Generative AI may seem like magic at first, but with a little Python, the PyTorch framework, and some practice, you can build interesting and useful models that will train and run on your laptop. This book shows you how. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the book\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e \u003ci\u003eLearn Generative AI with PyTorch\u003c\/i\u003e introduces the underlying mechanics of generative AI by helping you build your own working AI models. You'll begin by creating simple images using a GAN, and then progress to writing a language translation transformer line-by-line. As you work through the fun and fascinating projects, you'll train models to create anime images, write like Hemingway, make music like Mozart, and more. You just need Python and a few machine learning basics to get started. You'll learn the rest as you go! \u003cp\u003e\u003c\/p\u003e \u003cb\u003eWhat's inside\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e- Build an English-to-French translator\u003cbr\u003e - Create a text-generation LLM\u003cbr\u003e - Train a diffusion model to produce high-resolution images\u003cbr\u003e - Music generators using GANs and Transformers \u003cp\u003e\u003c\/p\u003e\u003cb\u003eAbout the reader\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e Examples use simple Python. No deep learning experience required. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the author\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e \u003cb\u003eMark Liu\u003c\/b\u003e is the founding director of the Master of Science in Finance program at the University of Kentucky. \u003cp\u003e\u003c\/p\u003eThe technical editor on this book was \u003cb\u003eEmmanuel Maggiori\u003c\/b\u003e. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eTable of Contents\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e Part 1\u003cbr\u003e 1 What is generative AI and why PyTorch?\u003cbr\u003e 2 Deep learning with PyTorch\u003cbr\u003e 3 Generative adversarial networks: Shape and number generation\u003cbr\u003e Part 2\u003cbr\u003e 4 Image generation with generative adversarial networks\u003cbr\u003e 5 Selecting characteristics in generated images\u003cbr\u003e 6 CycleGAN: Converting blond hair to black hair\u003cbr\u003e 7 Image generation with variational autoencoders\u003cbr\u003e Part 3\u003cbr\u003e 8 Text generation with recurrent neural networks\u003cbr\u003e 9 A line-by-line implementation of attention and Transformer\u003cbr\u003e 10 Training a Transformer to translate English to French\u003cbr\u003e 11 Building a generative pretrained Transformer from scratch\u003cbr\u003e 12 Training a Transformer to generate text\u003cbr\u003e Part 4\u003cbr\u003e 13 Music generation with MuseGAN\u003cbr\u003e 14 Building and training a music Transformer\u003cbr\u003e 15 Diffusion models and text-to-image Transformers\u003cbr\u003e 16 Pretrained large language models and the LangChain library\u003cbr\u003e Appendixes\u003cbr\u003e A Installing Python, Jupyter Notebook, and PyTorch\u003cbr\u003e B Minimally qualified readers and deep learning basics\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003eDr. \u003cb\u003eMark Liu\u003c\/b\u003e is a tenured finance professor and the founding director of the Master of Science in Finance program at the University of Kentucky. He has more than 20 years of coding experience, a Ph.D. in finance from Boston College.\u003cbr\u003e","brand":"Manning Publications","offers":[{"title":"Default Title","offer_id":50900316815634,"sku":"9781633436466","price":55.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_b52fd649-00b8-4748-a259-d3911e64b121.jpg?v=1738379349","url":"https:\/\/surprise-castle.myshopify.com\/products\/learn-generative-ai-with-pytorch-9781633436466","provider":"Surprise Castle","version":"1.0","type":"link"}