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Generative AI with Python and PyTorch
Generative AI with Python and PyTorch

Generative AI with Python and PyTorch: Hands-on projects and cutting-edge techniques using generative adversarial networks and LLMs , Second Edition

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Profile Icon Joseph Babcock Profile Icon Raghav Bali
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Early Access Early Access Publishing in Jan 2025
₱1284.99 ₱1836.99
eBook Jan 2025 500 pages 2nd Edition
eBook
₱1284.99 ₱1836.99
Paperback
₱2296.99
Subscription
Free Trial
Arrow left icon
Profile Icon Joseph Babcock Profile Icon Raghav Bali
Arrow right icon
Early Access Early Access Publishing in Jan 2025
₱1284.99 ₱1836.99
eBook Jan 2025 500 pages 2nd Edition
eBook
₱1284.99 ₱1836.99
Paperback
₱2296.99
Subscription
Free Trial
eBook
₱1284.99 ₱1836.99
Paperback
₱2296.99
Subscription
Free Trial

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Generative AI with Python and PyTorch

Generative AI with Python and PyTorch, Second Edition: Hands-on projects and cutting-edge techniques using generative adversarial networks and LLMs

Welcome to Packt Early Access. We’re giving you an exclusive preview of this book before it goes on sale. It can take many months to write a book, but our authors have cutting-edge information to share with you today. Early Access gives you an insight into the latest developments by making chapter drafts available. The chapters may be a little rough around the edges right now, but our authors will update them over time.

You can dip in and out of this book or follow along from start to finish; Early Access is designed to be flexible. We hope you enjoy getting to know more about the process of writing a Packt book.

  1. Chapter 1: An Introduction to Generative AI: ""Drawing"" Data from Models
  2. Chapter 2: Building Blocks of Deep Neural Networks
  3. Chapter 3: The Rise of Methods for Text Generation
  4. Chapter 4: NLP 2.0: Using Transformers to Generate Text
  5. Chapter 5: Foundations of LLMs
  6. Chapter 6: Open Source LLMs
  7. Chapter 7: Prompt Engineering
  8. Chapter 8: LLM Toolbox/Ecosystem
  9. Chapter 9: LLM Optimisation Techniques
  10. Chapter 10: Emerging Applications in Generative AI
  11. Chapter 11: Neural Networks Using VAEs
  12. Chapter 12: Image Generation with GANs
  13. Chapter 13: Style Transfer with GANs
  14. Chapter 14: Deepfakes with GANs
  15. Chapter 15: Diffusion Models and AI Art
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Key benefits

  • Implement real-world applications of LLMs and generative AI
  • Use PEFT and LoRA to fine-tune models with a subset of the model weights to speed up training
  • Enhance your LLM toolbox with Retrieval Augmented Generation (RAG) techniques, LangChain, and LlamaIndex
  • Purchase of the print or Kindle book includes a free eBook in PDF format

Description

Become an expert in generative AI through practical projects to leverage cutting-edge models for Natural Language Processing (NLP) and computer vision. Generative AI with Python and PyTorch, Second Edition, is your comprehensive guide to creating advanced AI applications. Leveraging Python, this book provides a detailed exploration of the latest generative AI technologies. From NLP to image generation, this edition dives into practical applications and the underlying theories that enable these technologies. By integrating the latest advancements and applications of large language models, this book prepares you to design and implement powerful AI systems that transform data into actionable insights. You’ll build your LLM toolbox by learning about various models, tools, and techniques, including GPT-4, LangChain, RLHF, LoRA, and retrieval augmented generation. This deep learning book shows you how to generate images and apply styler transfer using GANs, before implementing CLIP and diffusion models. Whether you’re creating dynamic content or developing complex AI-driven solutions, Generative AI with Python and PyTorch, Second Edition, equips you with the knowledge to use Python and AI to their full potential.

Who is this book for?

This book is for data scientists, machine learning engineers, and software developers seeking practical skills in building generative AI systems. A basic understanding of math and statistics and experience with Python coding is required.

What you will learn

  • Understand the core concepts behind large language models and their capabilities
  • Craft effective prompts using chain-of-thought, ReAct, and prompt query language to guide LLMs toward your desired outputs
  • Learn how attention and transformers have changed NLP
  • Optimize your diffusion models by combining them with VAEs
  • Build several text generation pipelines based on LSTMs and LLMs
  • Leverage the power of open-source LLMs, such as Llama and Mistral, for various tasks

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 31, 2025
Length: 500 pages
Edition : 2nd
Language : English
ISBN-13 : 9781835884454
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Product Details

Publication date : Jan 31, 2025
Length: 500 pages
Edition : 2nd
Language : English
ISBN-13 : 9781835884454
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Category :
Languages :
Tools :

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Table of Contents

3 Chapters
Generative AI with Python and PyTorch, Second Edition: Hands-on projects and cutting-edge techniques using generative adversarial networks and LLMs Chevron down icon Chevron up icon
1 Introduction to Generative AI: “Drawing” Data from Models Chevron down icon Chevron up icon
2 Building Blocks of Deep Neural Networks Chevron down icon Chevron up icon
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