Learn how generative AI works by building your very own models that can write coherent text, create realistic images, and even make lifelike music.
Learn Generative AI with PyTorch 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!
In Learn Generative AI with PyTorch you’ll build these amazing models:
• A simple English-to-French translator
• A text-generating model as powerful as GPT-2
• A diffusion model that produces realistic flower images
• Music generators using GANs and Transformers
• An image style transfer model
• A zero-shot know-it-all agent
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.
About the technology
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.
About the book
Learn Generative AI with PyTorch 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!
What's inside
• Build an English-to-French translator
• Create a text-generation LLM
• Train a diffusion model to produce high-resolution images
• Music generators using GANs and Transformers
About the reader
Examples use simple Python. No deep learning experience required.
About the author
Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky.
The technical editor on this book was Emmanuel Maggiori.
1145650485
Learn Generative AI with PyTorch 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!
In Learn Generative AI with PyTorch you’ll build these amazing models:
• A simple English-to-French translator
• A text-generating model as powerful as GPT-2
• A diffusion model that produces realistic flower images
• Music generators using GANs and Transformers
• An image style transfer model
• A zero-shot know-it-all agent
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.
About the technology
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.
About the book
Learn Generative AI with PyTorch 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!
What's inside
• Build an English-to-French translator
• Create a text-generation LLM
• Train a diffusion model to produce high-resolution images
• Music generators using GANs and Transformers
About the reader
Examples use simple Python. No deep learning experience required.
About the author
Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky.
The technical editor on this book was Emmanuel Maggiori.
Learn Generative AI with PyTorch
Learn how generative AI works by building your very own models that can write coherent text, create realistic images, and even make lifelike music.
Learn Generative AI with PyTorch 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!
In Learn Generative AI with PyTorch you’ll build these amazing models:
• A simple English-to-French translator
• A text-generating model as powerful as GPT-2
• A diffusion model that produces realistic flower images
• Music generators using GANs and Transformers
• An image style transfer model
• A zero-shot know-it-all agent
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.
About the technology
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.
About the book
Learn Generative AI with PyTorch 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!
What's inside
• Build an English-to-French translator
• Create a text-generation LLM
• Train a diffusion model to produce high-resolution images
• Music generators using GANs and Transformers
About the reader
Examples use simple Python. No deep learning experience required.
About the author
Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky.
The technical editor on this book was Emmanuel Maggiori.
Learn Generative AI with PyTorch 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!
In Learn Generative AI with PyTorch you’ll build these amazing models:
• A simple English-to-French translator
• A text-generating model as powerful as GPT-2
• A diffusion model that produces realistic flower images
• Music generators using GANs and Transformers
• An image style transfer model
• A zero-shot know-it-all agent
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.
About the technology
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.
About the book
Learn Generative AI with PyTorch 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!
What's inside
• Build an English-to-French translator
• Create a text-generation LLM
• Train a diffusion model to produce high-resolution images
• Music generators using GANs and Transformers
About the reader
Examples use simple Python. No deep learning experience required.
About the author
Mark Liu is the founding director of the Master of Science in Finance program at the University of Kentucky.
The technical editor on this book was Emmanuel Maggiori.
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Product Details
| ISBN-13: | 9781638356134 |
|---|---|
| Publisher: | Manning |
| Publication date: | 01/28/2025 |
| Sold by: | SIMON & SCHUSTER |
| Format: | eBook |
| Pages: | 432 |
| File size: | 20 MB |
| Note: | This product may take a few minutes to download. |
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