This project is a content-based product recommendation engine inspired by Amazon's "Customers who viewed this item also viewed" feature. It uses a dataset of product metadata and user interactions to suggest similar items based on product titles, brands, and categories using TF-IDF vectorization and cosine similarity.
🧠 Key Features
TF-IDF Vectorization of product titles and metadata
Cosine Similarity for recommending related products
Top-N Recommendations based on a given product index
Prototype View in HTML for exploring how recommendations work visually
💼 Use Cases
E-commerce platforms seeking lightweight, fast recommender systems
Entry-level ML/AI projects demonstrating explainable recommendation logic
Integration into product landing pages for dynamic upselling
🛠️ Tools & Libraries
Python
pandas, scikit-learn
HTML (for displaying results)