Build a Movie Recommendation System Using ML

Train a machine learning model that suggests movies based on a user’s past preferences. Think Netflix-style personalization, using a dataset like MovieLens. Actionable Steps & Guidance: Understand Recommendation Systems: You can build: Content-based (based on movie genres, etc.) Collaborative filtering (based on user behavior) Use the MovieLens Dataset: Download from GroupLens. Start with the small dataset (100k ratings). Train the Model: Use libraries like: Pandas for data cleaning Scikit-learn for similarity algorithms Surprise or LightFM for collaborative filtering Build a Simple Interface: Allow a user to select a movie and return recommendations. Document Clearly: Include a README.md with instructions, sample results, and screenshots.