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data-processing-pipelines

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Understanding the customer life cycle Acquiring customer data Applying big data concepts to your customer relationships Finding high propensity prospects Upselling by identifying related products and interests Generating customer loyalty by discovering response patterns Predicting customer lifetime value (CLV) Identifying dissatisfied customers …

  • Updated Oct 3, 2020
  • Jupyter Notebook

Successfully established a machine learning model using PySpark which can accurately classify whether a bank customer will churn or not up to an accuracy of more than 86% on the test set.

  • Updated Aug 4, 2024
  • Jupyter Notebook

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