Predictive modeling by computational algorithms to train models, predict futures, detect anomalies, recognize patterns, and optimize ROI. We use the latest computation and IT technologies to streamline data input and output and data computation.
Explore data patterns and group data points according to similarities and differentiations for huge amounts of data. This is an initial step of more complex analyses in fields of marketing, finance, life sciences, etc.
Train predictive models in Python package based on large amounts of data to achieve high accuracy. Use models to predict future events, discover cause and effect relationships, and develop strategies. Typical applications are in targeted marketing, loyalty development, loan lifetime prediction, disease prediction, etc.
Apply well trained models to automatically detect patterns and abnormal events. Furthermore, develop automatic product recommendations based on analytical logics and business rules to achieve cross-sell and up-sell.
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