Task:

Create a reference implementation of Spark MLLib in churn modeling project.

Solution:

We used Mahout Random Forest Classification and Spark MLLib Random Forest Regressions to predict the probability of churn of customers for online-shop.

Task:

Build simple web solution that displays realtime data using Cubism.js with Google Big Query database as datasource.

Solution:

We have built simple authorization, API for working with BigQuery, front-end controller for managing multiple graphs and simple static cubism.js graphs.

Task:

Develop d3 graph to display paid / unpaid work for men / women depending on the country / countries selected.

Solution:

We used NWD3 collection of components for d3.js, added responsiveness and cross-browser support.