Anish Mahapatra on Medium curated some lists

Anish Mahapatra

Anish Mahapatra

AI

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An overview of the RAG pipeline. For documents storage: input documents -> text chunks -> encoder model -> vector database. For LLM prompting: User question -> encoder model -> vector database -> top-k relevant chunks -> generator LLM model. The LLM then answers the question with the retrieved context.

Anish Mahapatra

MongoDB-Kafka

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Anish Mahapatra

Kubernetes, Kafka

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Anish Mahapatra

interview prep

2 stories

Anish Mahapatra

Interview Prep

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Anish Mahapatra

Anish Mahapatra

Senior AI & ML Engineer | Fortune 500 | Senior Technical Writer - Google me. Anish Mahapatra | https://www.linkedin.com/in/anishmahapatra/

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