Résumé
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:
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.
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.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Mannings publ. |
| Auteur(s) | Mark Liu |
| Parution | 12/12/2024 |
| Nb. de pages | 432 |
| Couverture | Broché |
| EAN13 | 9781633436466 |
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