There are 1 repository under churn-analytics topic.
ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification
Repositório para o #alurachallengedatascience1
Modelling with Tidymodels and Parsnip - A Tidy Approach to a Classification Problem
Predicting user churn for a mobile health app called Diabesties. Capstone project for Galvanize Phoenix Data Science Immersive, October 2017.
Churn Analyzer: Analyze and understand user churn rate in your PostgreSQL database effortlessly.
A sample churn prevention solution for an fintech app
Churn prediction project
Customer Churn Analysis in R: Logistic, Classification Tree, XGBoost, Random Forest.
Telecom Churn Prediction using Machine Learning models
Demo to showcase advanced analytics with SQL R Services
Project to predict retention of students in a study program up-to and beyond semester 6 based on scores, socio-economic & demography factors (like debt, gender, religion and race), transferred credits, family fee contributions, academic background, phone and email habits.
Repositório destinado a documentar o desafio de Data Science da Alura #alurachallengedatascience1
crowd analytix competition
Analysing the telecom customer churn data
ANN to predict churning rate
Importance of churn Analysis and some concept upon it
Business Science Case Study Rmarkdown
sample data set and queries for performing a churn analysis on an e-commerce website
This repository is about predicting the exit status of the customer of the bank using the other independent variables in the dataset.We are using a Artificial Neural Network as the model to train over the dataset.Go through the Notebook to find the relevant details , visualisations about the dataset. The ANN.py file contains the code for training the model.
Data Mining for Telco Customer Data Using SAS Miner
Churn rate visualizations in Python
Develop an overview dashboard for managers utilizing a telecom industry user churn dataset to present insights on the current churn situation.
Customer churn is a common analysis conducted by businesses since the cost of client retention is lower than the cost of acquiring new clients.
Worked on three use cases- Churn data analysis, Movie recommendation engine and Intrusion detection system.
Identifying factors that resulted in Customer Churn
Customer Churn Analytics with R of a telecommunications company.
News Publishing Company Project
NGO Fund Raising Attrition Churn Modelling
Telecom Project
Redução da taxa de evasão de clientes (Churn Rate)
This is task 2 of 3 from the Power BI PwC Switzerland Virtual Internship organized in partnership with Forage
ChurnRadar: Unveiling Customer Churn Patterns with Predictive Insights
Leverage HR measures to build a classification model and detect employees likely to leave the company
To predict behavior to retain customers