How to Use Vector Search to Build a Movie Recommendation App

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-use-vector-search-to-build-a-movie-recommendation-app . Learn how to build a semantic movie recommendation app using ScyllaDB’s vector search to find films by meaning, not just keywords. Check more stories related to programming at: https://hackernoon.com/c/programming . You can also check exclusive content about #scylladb-vector-search , #movie-recommendation-app , #semantic-search-tutorial , #vector-similarity-functions , #python-streamlit-app , #sentence-transformers , #ann-index-scylladb , #good-company , and more. This story was written by: @scylladb . Learn more about this writer by checking @scylladb's about page, and for more stories, please visit hackernoon.com . ScyllaDB’s new Vector Search lets developers build semantic search apps that understand meaning, not just text. This tutorial shows how to create a movie recommendation app using Sentence Transformers, Python, and Streamlit. It covers schema design, vector indexing, and ANN-based querying for fast, intelligent recommendations.