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

Customer Churn Analysis in R: Logistic, Classification Tree, XGBoost, Random Forest.

Churn prediction project

Telecom Churn Prediction using Machine Learning models

Demo to showcase advanced analytics with SQL R Services

crowd analytix competition

Repositório destinado a documentar o desafio de Data Science da Alura #alurachallengedatascience1

Analysing the telecom customer churn data

Importance of churn Analysis and some concept upon it

Business Science Case Study Rmarkdown

ANN to predict churning rate

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.

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 trainin…

Customer churn is a common analysis conducted by businesses since the cost of client retention is lower than the cost of acquiring new clients.

Data Mining for Telco Customer Data Using SAS Miner