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**Netflix Movie Recommendation System** is a machine learning–powered movie recommender that suggests personalized film recommendations based on a selected movie. Built using Python, Scikit-learn, and Streamlit, the system uses NLP techniques like Bag of Words and Cosine Similarity to identify similar movies and return the top 5 matches.

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Netflix Movie Recommendation System

Lights. Camera. Python. Action.
A machine-learning-powered movie recommender system that vibes like Netflix and delivers cinematic suggestions tailored just for you.


Project Overview

Ever sat for hours scrolling through movies and still ended up rewatching Friends?
Say no more. This recommender system is your personal Netflix genie, trained on real movie data to suggest what to watch next, based on your mood, taste, or favorite film.

It’s simple, sleek, and smart—just enter a movie name, and the engine fires up recommendations like magic. 🪄


Features

  • Search any movie and get top 5 similar recommendations
  • Optional genre filtering (wanna go rom-com or thriller? we gotchu)
  • Auto-fetch movie posters for better UI feels
  • Powered by Cosine Similarity and Bag of Words
  • Built with ML + NLP + Streamlit sauce

Tech Stack

Layer Tools / Libraries
Backend Python, Pandas, Scikit-learn
ML Engine CountVectorizer, Cosine Similarity
UI/Frontend Streamlit (clean + fast)
Data TMDB Movie Dataset (or Indian custom)

About

**Netflix Movie Recommendation System** is a machine learning–powered movie recommender that suggests personalized film recommendations based on a selected movie. Built using Python, Scikit-learn, and Streamlit, the system uses NLP techniques like Bag of Words and Cosine Similarity to identify similar movies and return the top 5 matches.

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