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hazard

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In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.

  • Updated Jan 21, 2022
  • Jupyter Notebook

It will be an Advanced Trading Suite, an implementation of HyperX, xLedger and Hazard. Much of the project is being learned and decided during development, so where the major version 0 (zero) appears, the minimum required for use has not yet been reached or completed.

  • Updated Nov 29, 2021

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