Technology stack: Django, Spark, Kafka, HDFS, Gobblin, MongoDB.
ECOMMERCE RECOMMENDATION ENGINE
ECOMMERCE RECOMMENDATION ENGINE
Business goal:
To provide personalized recommendations based on consumer and socio-economic profile and purchase intelligence to increase up-selling and cross selling opportunities and to design personalized targeting and retargeting campaigns
For more information, contact us
Challenge:
A personalized recommendation engine based on the following machine learning algorithms was developed:
- Collaborative Filtering – Matrix Factorization
- Semi Restricted Boltzmann Machines
- General Factorization Framework – Context-aware recommendations
- Alternating Least Squares (ALS) Learning
