Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Arrow up icon
GO TO TOP
Generative AI with Python and PyTorch

You're reading from   Generative AI with Python and PyTorch Navigating the AI frontier with LLMs, Stable Diffusion, and next-gen AI applications

Arrow left icon
Product type Paperback
Published in Mar 2025
Publisher Packt
ISBN-13 9781835884447
Length 454 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Joseph Babcock Joseph Babcock
Author Profile Icon Joseph Babcock
Joseph Babcock
Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Introduction to Generative AI: Drawing Data from Models FREE CHAPTER 2. Building Blocks of Deep Neural Networks 3. The Rise of Methods for Text Generation 4. NLP 2.0: Using Transformers to Generate Text 5. LLM Foundations 6. Open-Source LLMs 7. Prompt Engineering 8. LLM Toolbox 9. LLM Optimization Techniques 10. Emerging Applications in Generative AI 11. Neural Networks Using VAEs 12. Image Generation with GANs 13. Style Transfer with GANs 14. Deepfakes with GANs 15. Diffusion Models and AI Art 16. Unlock Your Exclusive Benefits 17. Other Books You May Enjoy
18. Index

Summary

Deepfakes are a complicated subject both ethically and technically. In this chapter, we discussed the deepfake technology in general to start with. We presented an overview of what deepfakes are all about and briefly touched upon a number of productive as well as malicious use cases. We presented a detailed discussion on different modes of operation of different deepfake setups and how each of these impacts the overall believability of generated content. While deepfakes is an all-encompassing term associated with videos, images, audio, text, and so on, we focused on visual use cases only in this chapter.

Given our scope, we discussed various feature sets leveraged by different works in this space. Particularly, we discussed the Facial Action Coding System (FACS), 3D morphable models (3DMM), and facial landmarks. We also discussed how we can perform facial landmark detection using libraries such as dlib and MTCNN. We then presented a high-level flow of tasks to be performed...

lock icon The rest of the chapter is locked
Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Generative AI with Python and PyTorch
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Modal Close icon
Modal Close icon