You're reading from Generative AI Foundations in Python Discover key techniques and navigate modern challenges in LLMs

Product type Paperback

Published in Jul 2024

Publisher Packt

ISBN-13 9781835460825

Length 190 pages

Edition 1st Edition

Languages

Python

Tools

Transfer learning

Concepts

Artificial Intelligence

Author (1):

Carlos Rodriguez

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Table of Contents (13) Chapters

Preface

1. Part 1: Foundations of Generative AI and the Evolution of Large Language Models FREE CHAPTER

2. Chapter 1: Understanding Generative AI: An Introduction

3. Chapter 2: Surveying GenAI Types and Modes: An Overview of GANs, Diffusers, and Transformers

4. Chapter 3: Tracing the Foundations of Natural Language Processing and the Impact of the Transformer

5. Chapter 4: Applying Pretrained Generative Models: From Prototype to Production

6. Part 2: Practical Applications of Generative AI

7. Chapter 5: Fine-Tuning Generative Models for Specific Tasks

8. Chapter 6: Understanding Domain Adaptation for Large Language Models

9. Chapter 7: Mastering the Fundamentals of Prompt Engineering

10. Chapter 8: Addressing Ethical Considerations and Charting a Path Toward Trustworthy Generative AI

11. Index

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References

This reference section serves as a repository of sources referenced within this book; you can explore these resources to further enhance your understanding and knowledge of the subject matter:

https://doi.org/10.1007/s11023-020-09526-7https://www.theguardian.com/technology/2019/feb/14/elon-musk-backed-ai-writes-convincing-news-fiction
Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., Anderson, H., Roff, H., Allen, G. C., Steinhardt, J., Flynn, C., Ó hÉigeartaigh, S., Beard, S., Belfield, H., Farquhar, S., & Amodei, D. (2018). The malicious use of artificial intelligence: Forecasting, prevention, and mitigation. arXiv [cs.AI]. http://arxiv.org/abs/1802.07228.
Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., Roberts, A., Brown, T., Song, D., Erlingsson, U., Oprea, A., & Raffel, C. (2020). Extracting training data from large language models...