Movie Recommendation System

• Recommend movies based on user preferences
• Find similar movies using similarity metrics
• Load and process movie datasets
• Display top recommended movies

Follow these steps in order. Each one builds on the previous.

1. Step 1

   Download and inspect a movie ratings dataset

2. Step 2

   Load the dataset using pandas

3. Step 3

   Clean and preprocess missing data

4. Step 4

   Organize movie features into a pandas DataFrame

5. Step 5

   Compare movies using cosine similarity

6. Step 6

   Build the recommendation function

7. Step 7

   Display top movie recommendations to the user

8. Step 8

   Test the recommendation system with sample inputs

• pandas documentation
• scikit-learn user guide
• MovieLens dataset
• Cosine Similarity