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Looking for correlations and making prediction in e-commerce system

Technologies: Python, Scikit-learn

Duration: 5 months

Implemented system that ranks customers making projections critical for business actions like upgrading from free to premium accounts, amounts of payments for premium accounts and how likely that person will stop using the service. The system is trained on a database of user account information and user series of actions made at the service. After the new user data is provided to system, a ranking based on projected future actions is produced.

We used the following techniques:

– feature engineering for machine learning;

– random forest/decision trees models;

– “bag of words” like model for user actions.

Clients
Category
Data Science, Machine Learning, Python
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