Project information
- Category: Web design
- Project date: Feb, 2019
- Project URL: Github
Bank Customer Churn Prediction Model
Build an end-to-end churn prediction model. Churn prediction is one of the most well known applications of machine learning and data science in the Customer Relationship Management (CRM) and Marketing fields. Simply put, a churner is a user or customer that stops using a company's products or services.
Project Requirements
Perform necessary steps to acheive a higher prediction rate.
- Find a good prediction model to help bank to know before hand the possibility of a customer leaving their bank.
- Implement several Supervised Algorithm.
- Find best suited machine learning to use for this problem.
Skills Required
Python
Pandas
numPy
seaborn
Logistic Regression
RandomForest Classifier
Decision Tree Model
Naive Bayes
Matplotlib
Support Vector Machine(SVM)
GradientBoosting Classifier
Techniques
Major Tasks
- Checking for Data summary, correlation, etc.
- Creating visualization to explore features correlation.
- Using OneHotEncoding to transform categorical variables into numerical.
- Comparing results of Logistic Regression, Decision Tree Model, RandomForest, Naive Bayes, Support Vector Machine(SVM), etc using accuracy score and f1 score.
Completed using Jupyter Notebook.