Part 2: Techniques for Tailoring LLMs

This section highlights key techniques that have emerged in recent years to customize Large Language Models (LLMs) for specific business needs, such as fine-tuning. It also addresses current challenges, including mitigating hallucinations and extending training cut-off dates, to incorporate up-to-date information through methods such as Retrieval Augmented Generation (RAG). Additionally, we will explore prompt engineering techniques to enhance effective communication with AI.

This part contains the following chapters:

• Chapter 3, Fine Tuning: Building Domain-Specific LLM Applications
• Chapter 4, RAGs to Riches: Elevating AI with External Data
• Chapter 5, Effective Prompt Engineering Strategies: Unlocking Wisdom Through AI