Fashion Recommendation

Retail

Background

The client runs a service that brings together designers and fashion enthusiasts. The client needed to increase the company’s revenue by suggesting products that the customers are likely to purchase.

Our work

We built a recommendation engine based on the user’s activity history. We designed interactions with the products and the media content. The recommendation engine was an ensemble of two machine learning algorithms.

The outcome

An advanced recommendation engine that can recommend popular/personalized products to the users.

Technology used
  • Python
  • Spark
  • Cassandra
  • AWS