Decoding Large Language Models
Decoding Large Language Models
An exhaustive guide to understanding, implementing, and optimizing LLMs for NLP applications
About the Book
Ever wondered how large language models (LLMs) work and how they're shaping the future of artificial intelligence? Written by a renowned author and AI, AR, and data expert, Decoding Large Language Models is a combination of deep technical insights and practical use cases that not only demystifies complex AI concepts, but also guides you through the implementation and optimization of LLMs for real-world applications.
You’ll learn about the structure of LLMs, how they're developed, and how to utilize them in various ways. The chapters will help you explore strategies for improving these models and testing them to ensure effective deployment. Packed with real-life examples, this book covers ethical considerations, offering a balanced perspective on their societal impact. You’ll be able to leverage and fine-tune LLMs for optimal performance with the help of detailed explanations. You’ll also master techniques for training, deploying, and scaling models to be able to overcome complex data challenges with confidence and precision. This book will prepare you for future challenges in the ever-evolving fields of AI and NLP.
By the end of this book, you’ll have gained a solid understanding of the architecture, development, applications, and ethical use of LLMs and be up to date with emerging trends, such as GPT-5.
About the Author
Table of Contents
- LLM Architecture
- How LLMs Make Decisions
- The Mechanics of Training LLMs
- Advanced Training Strategies
- Fine-Tuning LLMs for Specific Applications
- Testing and Evaluating LLMs
- Deploying LLMs in Production
- Strategies for Integrating LLMs
- Optimization Techniques for Performance
- Advanced Optimization and Efficiency
- LLM Vulnerabilities, Biases, and Legal Implications
- Case Studies – Business Applications and ROI
- The Ecosystem of LLM Tools and Frameworks
- Preparing for GPT-5 and Beyond
- Conclusion and Looking Forward
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