Customer Churn

Predicting Customer Churn

Pipeline

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   ├── figures        <- Generated graphics and figures to be used in reporting
│   ├── templates      <- EDA and Data Drift reports as html
│   ├── Dockerfile     <- Dockerfile for monitoring data drift
│   ├── Dockerfile_eda <- Dockerfile for EDA
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │    ├── load_data.py
│   │    ├── eda.py
│   │    ├── preprocess.py
│   │    ├── split_data.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── optimization.py
│   │   ├── train_model.py
│   │   ├── model_selection.py
│   │   ├── model_monitor.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
├── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io
├── tests              <- tests for python
├── webapp             <- folder for hosting model in production
├── dvc.yaml           <- DVC pipeline stages file
├── Jenkinsfile        <- Jenkins Pipeline file
├── requirements.txt   <- requirements for running this project
├── params.yaml        <- parameters configuration for this project
└── deployment         <- yaml files required for creating deployment in kubernetes

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