Decoding Large Language Models

Table of Contents

1. LLM Architecture
2. How LLMs Make Decisions
3. The Mechanics of Training LLMs
4. Advanced Training Strategies
5. Fine-Tuning LLMs for Specific Applications
6. Testing and Evaluating LLMs
7. Deploying LLMs in Production
8. Strategies for Integrating LLMs
9. Optimization Techniques for Performance
10. Advanced Optimization and Efficiency
11. LLM Vulnerabilities, Biases, and Legal Implications
12. Case Studies – Business Applications and ROI
13. The Ecosystem of LLM Tools and Frameworks
14. Preparing for GPT-5 and Beyond
15. Conclusion and Looking Forward