This module provides the user an ability to build a customised model based on the problem space the user is looking to solve problem in. Lets say user wants to build a very simple to complex regression model which is not part of other offering, user can select Regression module from the available below cards and setup experiment based on data and objective.


As a user we would like to run different ML experiments over the datasets so as to solve a given problem. The problem can vary from very specific to an absolutely generalized area based on the available dataset. As an example there can be problems which may not directly fit in use case like Supply Chain or Personalization, but can be fit into more ML way of problem definition like Classification, Regression, Time Series or Clustering. This module allows user to custom build models based on the type of Machine Learning model user would like to use.

Result/Use Cases

Different types of use cases we have used this module for are below

  • Classification: Propensity modelling, Fraud Detection/ Credit Default Customers/ Churn models
  • Regression: Basket Size Prediction/ ETA prediction of delivery
  • Time Series: Demand Forecasting/ Stock Market prediction/ Inventory Forecast
  • Clustering: Customer Segmentation/ Time Series CLassification
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