Learn generative ai with pytorch, mark liu
Описание
Learn how generative AI works by building your very own models that can write
Text generation with recurrent neural networks.
B Minimally qualified readers and deep learning basics
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
B Minimally qualified readers and deep learning basics
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
Python programming skills
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
bull; A text-generating model as powerful as GPT-2.
Learn Generative AI with PyTorch
Transformers, Generative Adversarial Networks (GANs), diffusion models, LLMs,
bull; A diffusion model that produces realistic flower images
laptop. This book shows you how
About the reader
You just need Python and a few machine learning basics to get started. You’ll
laptop. This book shows you how.
Get programming: learn to code with python, ana bell
B Minimally qualified readers and deep learning basics
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
Selecting characteristics in generated images!
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
GANs, Transformers, Large Language Models LLMs, variational autoencoders
bull; A diffusion model that produces realistic flower images.
the way, you’ll master the fundamentals of General Adversarial Networks
Mark Liu
Learn Generative AI with PyTorch
Selecting characteristics in generated images.
The technical editor on this book was
Emmanuel Maggiori
.
Table of Contents
Part 1
1 What is generative AI and why PyTorch?
2 Make python talk: build apps with voice control and speech recognition, mark liu
3 Generative adversarial networks: Shape and number generation
Part 2
4 bull; Create a text-generation LLM
5 Selecting characteristics in generated images
6 CycleGAN: Converting blond hair to black hair
7 is the founding director of the Master of Science in Finance program at the
Part 3
8 Text generation with recurrent neural networks
9 A line-by-line implementation of attention and Transformer
10 Training a Transformer to translate English to French
11 Training a Transformer to translate English to French
12 Training a Transformer to generate text
Part 4
13 create anime images, write like Hemingway, make music like Mozart, and more
14 is the founding director of the Master of Science in Finance program at the
15 Diffusion models and text-to-image Transformers
16 You just need Python and a few machine learning basics to get started. You’ll
Appendixes
B Minimally qualified readers and deep learning basics
Read more
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