Customer-Churn-Prediction

Customer Churn Prediction model created based on Classification algorithms created with reference to DataTalks.Club mlzoomcamp course created using Google Colab

Dataset: https://raw.githubusercontent.com/alexeygrigorev/mlbookcamp-code/master/chapter-03-churn-prediction/WA_Fn-UseC_-Telco-Customer-Churn.csv

1. Data Preparation

Reading the data from csv file and checking for null values and examining important features.

2. Exploratory Data Analysis

• Examining important features using mutual information(MI) scores.
• Changing categorial variables to numerical variables using one hot encoding and pandas dummy
• Checking correlation with numerical variables

3. Model

Models
Logistic Regression
Random Forest classifier
XGB classifier

Picking the best model based on maximum Accuracy

Predicting the customer churn using the final model with test data