Movie Recommender System

• Tech Stack: Streamlit, Python, numpy, Sklearn(CountVectorizer, cosine_similarity), pandas
• Website URL: Link
• Github URL: Project Link

The main goal of this project is to recommend the 5 movies based on user interest.

In today’s technology driven world, recommender systems are socially and economically critical for ensuring that individuals can make appropriate choices surrounding the content they engage with on a daily basis. One application where this is especially true surrounds movie content recommendations; where intelligent algorithms can help viewers find great titles from tens of thousands of options.

Providing an accurate and robust solution to this challenge has immense economic potential, with users of the system being exposed to content they would like to view or purchase - generating revenue and platform affinity.