Amazon Product Recommender System
Budget: $30 – $250 USD
build a recommender system using Amazon data. IN PYTHON
Amazon Recommender System
Data: http://snap.stanford.edu/data/amazon-meta.html
The data was collected by crawling Amazon website and contains product metadata and review
information about 548,552 different products (Books, music CDs, DVDs and VHS video tapes).
Suggested Problem: Implement a data analytics engine that has the following functions:
1. Search.
The search engine can answer simple and complex queries. Searchable attributes include but
not limited to:
Best n sellers of a certain category
Number of reviews of a product
Queries with enriched operators: >, >=, =, <, <=; e.g., Select movie with average
rating >=4.5
The number of customers co-purchasing same product of a user.
2. Recommender
Analyze the co-purchasing patterns in the data. Given a customer, recommend products that the
customer are most likely interested.
Amazon Recommender System
Data: http://snap.stanford.edu/data/amazon-meta.html
The data was collected by crawling Amazon website and contains product metadata and review
information about 548,552 different products (Books, music CDs, DVDs and VHS video tapes).
Suggested Problem: Implement a data analytics engine that has the following functions:
1. Search.
The search engine can answer simple and complex queries. Searchable attributes include but
not limited to:
Best n sellers of a certain category
Number of reviews of a product
Queries with enriched operators: >, >=, =, <, <=; e.g., Select movie with average
rating >=4.5
The number of customers co-purchasing same product of a user.
2. Recommender
Analyze the co-purchasing patterns in the data. Given a customer, recommend products that the
customer are most likely interested.