Recommendation System Based on User Behavior Data Analytics

This project aims to build a recommendation system by analyzing user behavior data. The objective is to suggest relevant products or content using data analytics techniques to improve user experience and engagement.

Collect user interaction datasets.

Perform data preprocessing and normalization.

Analyze user preferences and behavior patterns.

Implement collaborative or content-based filtering.

Evaluate recommendation accuracy.

Visualize recommendation results.

Document system design and findings.