AJAX-Movie-Recommendation-System-with-Sentiment-Analysis

Why we included this project

Here's a working example of a content-based movie recommender paired with review sentiment analysis, all inside a Flask web app. It pulls movie metadata from the TMDB API, builds a cosine-similarity model over text features to surface films similar to the one a user picks, then scrapes IMDB reviews with BeautifulSoup to gauge how people felt about that title. That combination is useful for developers and students who want to see a recommender and a text-classification step fit together in one system rather than as isolated notebooks. It runs locally once you grab a free TMDB key, and the code is readable enough to adapt to other domains. It's also a decent reference for anyone learning to wire a machine-learning pipeline into a browser-facing interface with AJAX.