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Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.
A minimal project to understand how cosine similarity works in a vector database 🧠📊. It demonstrates semantic search by converting text into embeddings and comparing them using vector math.
A high-performance job recommendation system built with TypeScript, Express, TypeORM, and PostgreSQL. The system uses vector embeddings and cosine similarity to provide accurate, personalized job recommendations at scale.
Job matching platform using custom TF-IDF + spaCy NLP. Built to learn ML fundamentals and full-stack dev with Next.js & FastAPI. Upload CV, get matched with jobs, generate AI cover letters.