WTTE-RNN a framework for churn and time to event prediction
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Updated
Aug 7, 2020 - Python
WTTE-RNN a framework for churn and time to event prediction
Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.
Showcase for using H2O and R for churn prediction (inspired by ZhouFang928 examples)
Using an afticial neural network to predict customers who leave the bank.
Build an scikit-learn model to predict churn using customer telco data.
An End to End Customer Churn Prediction solution using AWS services.
零售电商客户流失模型,基于tensorflow,xgboost4j-spark,spark-ml实现LR,FM,GBDT,RF,进行模型效果对比,离线/在线部署方式总结
Machine Learning to predict the possibility of customer churning
This repository will have all the necessary files for machine learning and deep learning based Banking Churn Prediction ANN model which will analyze tha probablity for a customer to leave the bank services in near future. Deployed on Heroku.
Predicting Customer Churn; simple approach using random forest
The python notebook is on googles new collabatory tool. Its a churn model being run on 3 different algorithms to compare.
Feature Engineering and Churn Prediction on Telecom data
Customer churn prediction for telecom dataset
Churn prediction using Artificial Neural Network
This repository contains a starter notebook for the DSN PreBootcamp Expresso Churn Hackathon
Extracted live tweets of customers by using Twitter APIs to create automatic rule-based churn detection algorithm for Verizon, AT&T and T-Mobile.
A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.
This repository consists of predicting dynamic pricing, churn predictions using sales and marketing data for understanding users' behaviour.
Streamlit based web application for churn prediction
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