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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

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Product type Paperback
Published in Mar 2025
Publisher Packt
ISBN-13 9781835884447
Length 450 pages
Edition 2nd Edition
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Authors (2):
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Joseph Babcock Joseph Babcock
Author Profile Icon Joseph Babcock
Joseph Babcock
Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
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Toc

Table of Contents (18) Chapters Close

Preface 1. Introduction to Generative AI: Drawing Data from Models 2. Building Blocks of Deep Neural Networks FREE CHAPTER 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. Other Books You May Enjoy
17. Index

Key feature set

The human face and body are key entities in the task of fake content generation. While deep learning architectures usually do not require hand-crafted features, a little nudge goes a long way when complex entities are involved. Particularly when dealing with the human face, apart from detecting the overall face in a given image/video, a deepfake solution also needs to focus on the eyes, mouth, and so on. We discussed different modes of operation in the previous section, where we highlighted the importance of different sections of a face and their impact on improving the believability of generated fake content.

Facial landmarks

Facial landmarks are a list of important facial features such as the nose, eyebrows, mouth, the contours of the eyes, and so on. The goal is the detection of these key features using some form of a regression model. The most common method is to leverage a predefined set of positions on the face or body that can be efficiently tracked...

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