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rag.txt | RAG means Retrieval-Augmented Generation.
It combines information retrieval with language generation.
The retriever finds relevant context from a knowledge base,
and the generator uses this context to answer questions more accurately. |
docker.txt | Docker provides containers to package applications together with their dependencies.
This ensures consistent environments across development, testing, and production.
In AI/ML projects, Docker helps teams run the same code everywhere without conflicts. |
rag.pdf | RAG means Retrieval-Augmented Generation. It combines information retrieval with language generation. The retriever 铿乶ds relevant context from a knowledge base, and the generator uses this context to answer questions more accurately. |
mlops.txt | MLOps combines machine learning with DevOps practices.
It automates model training, deployment, monitoring, and versioning.
The main goal is to make ML models reproducible, scalable, and reliable in production. |
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