Predict Customer Churn

• Project Predict Customer Churn of ML DevOps Engineer Nanodegree (Udacity)

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Project Description

TODO: Describe the purpose of this project in your own words.

You should include:

• What problem this project solves
• What the machine learning pipeline does
• What models are used

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Files and Data Description

TODO: Describe the main files and dataset used in this project.

Main Files

• churn_library.py

  TODO: Explain what this file does

• churn_script_logging_and_tests.py

  TODO: Explain what this file does

• churn_notebook.ipynb

  TODO: Explain the role of this notebook

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Data

• data/bank_data.csv

  TODO: Describe the dataset (features, target, etc.)

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Output Directories

After running the project, outputs will be saved to:

• EDA images → images/eda/
• Model results → images/results/
• Models → models/
• Logs → logs/churn_library.log

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Running the Files

1. Run the Pipeline

python churn_library.py

TODO: Briefly describe what happens when this script runs

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2. Run Tests and Logging

python churn_script_logging_and_tests.py

TODO: Explain what the test script does and what is logged

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Expected Outputs

TODO: List and describe the expected outputs of the project

Minimum expected outputs:

• Models:

  • models/rfc_model.pkl
  • models/logistic_model.pkl

• Images:

  • EDA plots in images/eda/
  • Model evaluation plots in images/results/

• Logs:

  • logs/churn_library.log

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Notes

TODO: Add any additional notes or assumptions about your implementation

Examples:

• How logging is handled
• Any assumptions about the dataset
• Any limitations of the model