Project Overview

The Movie Recommendation System is a web-based application that recommends movies to users based on their selected movie preferences. The project uses a recommendation algorithm to identify and suggest movies that are similar to the user's chosen movie.

Features

Simple and user-friendly interface
Search and select a movie
Provides similar movie recommendations
Helps users discover new movies
Interactive web application
Fast and easy-to-use recommendation system

Technologies Used

Python
Streamlit
Pandas
NumPy
Machine Learning / Recommendation Algorithm

How It Works

The user selects a movie from the application. The system processes the selected movie and compares its characteristics with other movies in the dataset. Based on the similarity between movies, the system generates a list of recommended movies for the user.

Objective

The main objective of this project is to build a simple and effective movie recommendation system that helps users discover movies according to their interests and preferences.

Conclusion

This project provided practical experience in Python, data processing, recommendation systems, and Streamlit application development. It demonstrates how machine learning and data analysis techniques can be used to create personalized recommendation systems.