Movie Recommendation System Project Using Content-Based Filtering

Movie Recommendation System Project Using Content-Based Filtering

Learn how to build an intelligent movie recommendation system using Machine Learning that suggests similar movies based on genres and average user ratings. This beginner-friendly handbook guides you through data handling, content-based filtering, KNN similarity, and deploying an interactive recommender using Gradio.

Movie Recommendation System – Machine Learning Project

This handbook helps learners gain hands-on experience in machine learning by building a complete movie recommendation system from scratch. It explains how to use genre similarity and average ratings to recommend movies, covering data preprocessing, TF-IDF, KNN, and simple deployment in a clear and beginner-friendly way.

Movie Recommendation System – Machine Learning Project for Beginners

This project is ideal for beginners who want to get started with machine learning and data science. It’s perfect for students, freshers, and anyone with basic Python knowledge who wants to understand how real-world recommendation systems work using practical, hands-on implementation.

Prerequisites

This course is suitable for:

• Basic knowledge of Python programming
• Basic understanding of Machine Learning concepts
• A Google account to access Google Colab
• A Kaggle account to download the movie dataset
• Internet connection to access datasets and run the project