To predict whether the customers will subscribe to the system after 1-month free trial or not.

Google Developer Group Ahmedabad - Machine Learning for Imbalanced Class Distributions Session code

🛒 Customer Churn Prediction.

The objective is to build a classifier for prediction of customer churn.

Stanford Continuing Studies course "Data-Driven Marketing" by Angel Evan, Consultant. Completed Winter 2017-2018

Explored models such as Logistic Regression (SMOTE), SVM, RandomForest & XGBoost to assess customers’ propensity or risk to churn for a telecom. Performed In-depth EDA & data preprocessing in Python.

Customer churn prediction using Neural Networks with TensorFlow.js

Telecom Customer segmentation and Churn Prediction

Telecom customer churn example with h2o

EDA & prediction of customer churn at Orange.

Customer Churn Prediction using PyCaret.

Customer churn prediction is to measure why customers are leaving a business. We will build a deep learning model to predict the churn.

The purpose of this assignment is to use SAS Machine Learning Platform - SAS Vyia to explore data, preform customer segmentation and predict customer churn.

Customer churn, also known as customer attrition, occurs when customers stop doing business with a company. The companies are interested in identifying segments of these customers because the price for acquiring a new customer is usually higher than retaining the old one. A Deep Neural Network is employed to achieve this task.

Repository for Algoritma Show: Customer Churn Prediction

The goal of this project was to utilize classification models to predict whether or not a customer would churn. I went through the entire machine learning pipeline, discovered drivers of churn, and created many different models. Ultimately, my best Random Forest Classifier model was able to predict churned customers with an accuracy of about 80%.

Predicting customer churn using ANN and dealing with imbalanced data.

Machine-Learning-1