/udacity_customer_churn

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Predict Customer Churn

  • Project Predict Customer Churn of ML DevOps Engineer Nanodegree Udacity

Project Description

This is the first project of the ML DevOps Engineer Nanodegree Udacity.

Kitten

The project was created using the Streamlit as the frontend. In this way is possible to visualize the output easier.

Installing the project

This project uses Pipenv. In your root folder, open a terminal and enter:

pip install pipenv
pipenv install

Running Files

Using the model

  1. Download the data from Kaggle's Credit Card customers, save it in ./data/external/ folder and rename it to bank_data.csv.

  2. Open a terminal in the root folder and use the following command to initiate the web app in your local machine:

    streamlit run main.py

  3. Open the localhost:8501 in your browser.

IMPORTANT! Before running the line above, you need to install the project (see the section Installing the project ).

Testing the model

  1. Run the following command in terminal and within the virtual env:

    ipython churn_script_logging_and_tests_solution.py