Yash Jain

Practical RAG evaluation pipeline using RAGAS with metrics like faithfulness, context precision/recall, and answer relevancy.

A complete LangChain learning series with hands‑on Jupyter notebooks — covering prompts, output parsers, runnables, memory, tools, agents, and RAG — organized alongside an in‑depth YouTube playlist.

A complete RAG (Retrieval-Augmented Generation) learning series with hands-on Jupyter notebooks — covering document loading and chunking, embeddings and vector stores, retrieval strategies, reranking, query transformation, and advanced RAG pipelines — organized alongside an in-depth YouTube playlist.

A complete LangGraph learning series with hands-on Jupyter notebooks — covering graph-based workflows, state management, nodes and edges, agents, tool orchestration, and advanced RAG pipelines — organized alongside an in-depth YouTube playlist.

A complete Microsoft Agent Framework learning series with hands-on examples — covering agent setup, instructions, tool calling, MCP integration, multi-agent orchestration, conditional routing, state persistence, human-in-the-loop, evaluation, and production deployment in Python — organized alongside an in-depth YouTube playlist.

A complete Pydantic AI learning series with hands-on examples — covering type-safe agent workflows, structured outputs, dependency injection, tools, multi-agent systems, evaluation, and advanced GenAI orchestration in Python — organized alongside an in-depth YouTube playlist.