https://github.com/dwade-eng/amazon-product-recommender-prototype-
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.
https://github.com/dwade-eng/amazon-product-recommender-prototype-
html numpy pandas python3 scikit-learn
Last synced: 4 months ago
JSON representation
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.
- Host: GitHub
- URL: https://github.com/dwade-eng/amazon-product-recommender-prototype-
- Owner: dWADE-ENG
- Created: 2025-09-21T23:08:52.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-09-21T23:11:19.000Z (5 months ago)
- Last Synced: 2025-09-22T01:10:31.076Z (5 months ago)
- Topics: html, numpy, pandas, python3, scikit-learn
- Language: HTML
- Homepage:
- Size: 197 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Amazon-Product-Recommender-Prototype-
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)