This repository serves as an interview preparation guide for ML/AI engineering roles, containing battle-tested study materials across multiple domains. It includes implementations of ML algorithms from scratch (neural networks, traditional ML), LLM/GenAI fundamentals and production guides, production RAG system designs, agentic AI architecture examples, and system design scenarios for distributed ML. The content spans coding interview prep, system design master guides, and MLOps best practices.