Part 2: Tools and Strategies in LLMOps

Part two covers the practical aspects of implementing LLMOps, focusing on the critical stages of data management, including collection, transformation, and preparation, which are essential for training effective LLMs. Then, we explore the steps involved in model development, from feature creation to hyperparameter tuning. Finally, we address the crucial aspects of evaluating model performance, securing models, and ensuring they comply with legal and regulatory standards. This section provides a comprehensive look at the operational processes that ensure LLMs are both effective and adhere to required norms and practices.

This part contains the following chapters:

• Chapter 3, Processing Data in LLMOps Tools
• Chapter 4, Developing Models via LLMOps
• Chapter 5, LLMOps Review and Compliance