The "LLM Engineer's Handbook: Master the art of engineering large language models from concept to production" offers a comprehensive guide to building and deploying LLM applications. It covers essential topics such as MLOps, machine learning fundamentals, data science principles, and software engineering best practices. The handbook also delves into practical aspects like cloud computing on platforms such as AWS, Azure, and Google Cloud Platform, as well as containerization technologies like Kubernetes and Docker. AI
IMPACT Provides a structured curriculum for developing and deploying large language models in production environments.
RANK_REASON The item describes the contents of a handbook related to LLM engineering, which falls under research and development in the AI field. [lever_c_demoted from research: ic=1 ai=1.0]
- AWS
- Azure
- data science
- Docker
- Google Cloud Platform
- Kubernetes
- large-language models
- LLM Engineer's Handbook: Master the art of engineering large language models from concept to production
- machine learning
- MLOps
- Python
- software engineering
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