🎬Production-Ready Movie Recommendation System | Netflix

This podcast and article offer a comprehensive guide to constructing a production-ready movie recommendation system, similar to Netflix, utilizing Amazon Web Services.

It details the architecture, incorporating vector search with FAISS (a plan for future Pinecone integration), advanced embedding techniques using a two-tower model, and deployment via Docker and Kubernetes.

The article attached here covers essential aspects such as data ingestion, user interaction tracking, embedding generation, API development, and infrastructure setup, emphasizing scalability, performance, security, and operational best practices.

Furthermore, it outlines strategies for transitioning to a managed vector database and ensuring the system's reliability and cost-effectiveness.

Ultimately, this resource offers a practical blueprint for building and deploying a sophisticated recommendation engine.

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