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AI is being revolutionized by large language models (LLMs), but scaling its implementation is difficult. In the absence of an appropriate operational framework, business effect stalls, expenses increase, and models diverge.
By considering LLMs as enterprise assets rather than experiments, Applied LLMOps shows how to get over these challenges. The entire lifespan of LLM operations will be covered therein, from data sourcing and cleansing to fine-tuning, deployment, monitoring, and retraining. Additionally, you will learn how to manage bias, maintain compliance, optimize infrastructure, and protect security.
Using the techniques in this book will enable you to: