GitHub repository: satz2000/End-to-end-project---Customer-churn
Primary language: Jupyter Notebook
Created: 2021-09-27T04:58:10Z
Description: End to end projects-- Customer Churning prediction using Gradient Boost Classifier Algorithm perform pre-processing steps then fit data into the Algorithm and Hyper Parameter Tunning to reduce TN & FN value to perform our model to works with a new data. Finally deploying the model using Flask API