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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

References

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  3. Chen, Mark, Jerry Tworek, Heewoo Jun, et al. 2021. “Evaluating Large Language Models Trained on Code.” arXiv. https://arxiv.org/abs/2107.03374.
  4. Scientific Reports. 2019. “Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.” https://www.nature.com/articles/s41598-019-42294-8.
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  6. Google DeepMind. 2019. “AlphaStar: Grandmaster Level in StarCraft II Using Multi-Agent Reinforcement Learning.” https://deepmind.com/blog/article/AlphaStar-Grandmaster-level-in-StarCraft-II-using-multi-agent-reinforcement-learning.
  7. Devlin, Jacob, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. “BERT: Pre-Training of Deep Bidirectional Transformers for Language Understanding.” arXiv. https://arxiv.org/abs/1810.04805.
  8. Fox News. 2018. “Terrifying High-Tech Porn: Creepy ‘Deepfake’ Videos Are on the Rise.” https://www.foxnews.com/tech/terrifying-high-tech-porn-creepy-deepfake-videos-are-on-the-rise.
  9. Deepfake Image Sample. Wikimedia. https://upload.wikimedia.org/wikipedia/en/thumb/7/71/Deepfake_example.gif/280px-Deepfake_example.gif.
  10. A Chatbot Dialogue Created Using GPT-2. Devopstar. https://devopstar.com/static/2293f764e1538f357dd1c63035ab25b0/d024a/fake-facebook-conversation-example-1.png.
  11. OpenAI. 2019. “Better Language Models and Their Implications.” OpenAI Blog. https://openai.com/blog/better-language-models/.
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  15. Jebara, Tony. 2004. Machine Learning: Discriminative and Generative. Kluwer Academic (Springer).
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  18. Bayes, Thomas, and Richard Price. 1763. “An Essay towards Solving a Problem in the Doctrine of Chance.” Philosophical Transactions of the Royal Society of London 53: 370–418.
  19. Ho, Tin Kam. 1995. “Random Decision Forests.” Proceedings of the 3rd International Conference on Document Analysis and Recognition, Montreal, QC, August 14–16, 1995, 278–282.
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  23. Kingma, Diederik P., and Max Welling. 2022. “Auto-Encoding Variational Bayes.” arXiv. https://arxiv.org/abs/1312.6114.
  24. Sample Images from a VAE: https://miro.medium.com/max/2880/1*jcCjbdnN4uEowuHfBoqITQ.jpeg
  25. Chen, Ricky T. Q., Xuechen Li, Roger Grosse, and David Duvenaud. 2019. “Isolating Sources of Disentanglement in VAEs.” arXiv Vanity. https://www.arxiv-vanity.com/papers/1802.04942/.
  26. Esser, Patrick, Johannes Haux, and Björn Ommer. 2019. “Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis.” arXiv. https://arxiv.org/pdf/1910.10223.pdf.
  27. CycleGANs Apply Stripes to Horses to Generate Zebras.” GitHub. https://github.com/jzsherlock4869/cyclegan-pytorch?tab=readme-ov-file.
  28. Bourached, Anthony, and George Cann. 2019. “Raiders of the Lost Art.” arXiv. https://arxiv.org/pdf/1909.05677.pdf.
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  35. X post: https://x.com/TonyHoWasHere/status/1636347961813655557.
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  37. Gupta, Anant, Srivas Venkatesh, Sumit Chopra, and Christian Ledig. 2019. “Generative Image Translation for Data Augmentation of Bone Lesion Pathology.” Proceedings of Machine Learning Research. https://proceedings.mlr.press/v102/gupta19b.html.
  38. Mulé, Sébastien, Littisha Lawrance, Younes Belkouchi, and Valérie Vilgrain. 2022. “Generative Adversarial Networks (GAN)-Based Data Augmentation of Rare Liver Cancers: The SFR 2021 Artificial Intelligence Data Challenge.” ScienceDirect. https://www.sciencedirect.com/science/article/pii/S2211568422001711.
  39. Shapiro, Danny. 2023. “Generative AI Revs Up New Age in Auto Industry, from Design and Engineering to Production and Sales.” NVIDIA Blog. https://blogs.nvidia.com/blog/generative-ai-auto-industry/.
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