🎬 Movie Recommendation System using Machine Learning

Recently, I built a movie recommendation system as part of my learning in Artificial Intelligence and Machine Learning.

The idea is simple — when a user enters a movie name, the system suggests similar movies.

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💡 Why I Built This

While learning machine learning, I wanted to build something practical instead of just studying theory.

Recommendation systems are used in platforms like Netflix and YouTube, so I thought it would be a good project to understand how they work.

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🚀 What the Project Does

The system takes a movie name as input and recommends similar movies based on:

• overview (story)
• genres
• keywords
• cast
• director

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🧠 How It Works (Simple)

• Combine all movie details into one text
• Convert text into numbers using TF-IDF
• Find similarity between movies using cosine similarity
• Return top 5 similar movies

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🛠 Tech Used

• Python
• scikit-learn
• pandas
• Flask
• HTML, CSS, JavaScript

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🔄 How It Works

1. User enters a movie name
2. Request goes to Flask backend
3. Model finds similar movies
4. Results are shown on screen

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🧪 What I Learned

• basics of recommendation systems
• NLP and text processing
• TF-IDF and similarity
• how to connect ML with a web app

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🔗 GitHub

https://github.com/alenkurian-ml/Content-Based-Movie-Recommendation

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📌 Final Thoughts

This is a simple project, but it helped me understand how recommendation systems actually work.

I’m still learning and building projects step by step.

Thanks for reading 🙂