Churn-Model

An end to end implementation of project which includes analysis of bank customer churn data as well as it prediction using various Machine Learning Models.

1. Churn Model.ipynb is a Jupyter Notebook consisting of:
   a. Exploratory Data Analysis of Churn Dataset.
   b. Method for dealing with imbalance in the dataset.
   c. Creating and testing Models for Churn Prediction.
   

2. Churn Model.pdf and Churn Model.html are pdf and html files respectively of Churn Model.ipynb jupyter notebook for proper viewing and displaying of plots created using Plotly.
   

3. churn.py is python file consisting of code for creating a basic Dashboard which displays interacive Data Visualizations using Dash library.
   

4. assets is a folder consisting of css templates used in the creation of Dashboard. Dash library requires this folder for implementing CSS.
   

5. Churn_Modelling.csv is dataset used for the project.
   
6. rfmodel.py consists of python code for Random Forest and is used for predicting when the model is deployed.
   
7. stl.py consists of python code for deploying the Random Forest model using streamlit library.