Predict Customer Churn

• Project Predict Customer Churn of ML DevOps Engineer Nanodegree Udacity

Project Description

This project aims to build a comprehensive library for predicting customer churn using machine learning models. The library includes functions for data loading, exploratory data analysis (EDA), feature encoding, feature engineering, model training and evaluation. The project leverages Python and popular data science libraries such as pandas, scikit-learn, seaborn and matplotlib.

Files and data description

The project contains the following main components:

• import_data: Function to load data from a CSV file.
• perform-eda: Function to perform exploratory data analysis and save generated plots.
• encode_helper: Function to encode categorical features.
• perform_feature_engineering: Function to split data into training and testing sets.
• train_models: Function to train and evaluate machine learning models (RandomForest and Logistic Regression).

Running Files

To set up the project and install the necessary dependencies, follow these steps:

• Install the required packages:

pip install -r requirements3.6.txt

• Run the files

python churn_library.py

python churn_script_logging_and_tests.py