rajaharsha / Amazon-Product-Recommendation-CF-ALS-Spark

We have chosen Amazon product sales data set comprising of sales activity and user ratings for each product. The idea is to create a product suggestion/recommendation system for each user based on his previous purchases and his rating for each one. A Collaborative Filtering model is built to predict the virtual ratings for the product that the user did not purchase. The system predicts the user rating for all the items and we display the products which user may be like, buy and rate higher.

AmazonProductRecommendation-CF-ALS-Spark

We have chosen Amazon product sales data set comprising of sales activity and user ratings for each product. The idea is to create a product suggestion/recommendation system for each user based on his previous purchases and his rating for each one. A Collaborative Filtering model is built to predict the virtual ratings for the product that the user did not purchase. The system predicts the user rating for all the items and we display the products which user may be like, buy and rate higher.

Demo

https://drive.google.com/file/d/0B3IrI8MNjGNVZ19jMUhZbHhYYmM/view?usp=sharing

Results Discussion

https://drive.google.com/file/d/0B3IrI8MNjGNVLVJEbHc1TlQ1ekE/view?usp=sharing