Unlock actionable insights and boost customer retention with this Power BI project. Analyze and visualize risk factors to proactively prevent churn. ➡️

Business Case Study to predict customer churn rate based on Artificial Neural Network (ANN), with TensorFlow and Keras in Python. This is a customer churn analysis that contains training, testing, and evaluation of an ANN model. (Includes: Case Study Paper, Code)

This repository contains analysis of churn in telephone service company (using IV and WOE), comparison of effect size and information value and quick tutorial how to use information value module (created for this analysis).

A Cognitive Code Complexity Analysis Tool. Cognitive complexity measures how hard it is for a human to understand the code, while cyclomatic complexity measures how hard your code is to test. Understandability is a huge cost factor because ~80% time is spent on reading and understanding code.

Churn analysis library

This project aims to conduct an analysis of costumers behavior and perception of the brand, by implementing different marketing analytics techniques and methods: RFM (recency, frequency, monetary) model, churn classification, MBA (market basket analysis) and sentiment analysis.

Churn Analyzer: Analyze and understand user churn rate in your PostgreSQL database effortlessly.

Curso de Deep Learning con Tensorflow + Keras

Analyzing customer attrition & strategies to reduce churn via AutoML techniques & PowerBI

A production-style event analytics system focused on immutable event modeling, SQL-driven metrics, retention, and funnel analysis.

Application pour analyser et prédire le churn client avec visualisations interactives

This repository contains a curated collection of intermediate-level projects showcasing skills in data cleaning, analysis, visualization, and business insights.

Customer Churn Analysis for a website

A project demonstrating how to predict customer churn based on product usage behaviours.

Command line tool to generate actionable metrics for priorizing refactors on your rust project

visualisation of churn data of a bank

Machine-Learning-1

Exploratory data analysis of datasets available in Kaggle.(IPL dataset, Zomato dataset, Loan dataset, Telecom customer churn dataset)

A churn model is a mathematical representation of how churn impacts your business. Churn calculations are built on existing data (the number of customers who left your service during a given time period). A predictive churn model extrapolates on this data to show future potential churn rates.

Churn rate analysis with artificial neural network.

Challenge de Data Science desenvolvido pela Alura, para montar um conjunto de análises e modelos de machine learning supervisionado para auxiliar o time de vendas da empresa Alura Voz a fidelizar clientes.

A machine learning project that predicts customer churn using the Telco dataset.

Analytical exploration of ecommerce customer behavior (2020–2023) using Tableau, covering segmentation, churn patterns, return impact, and revenue forecasting.

SmurphCast – percentage‑first time‑series forecasting (churn, CTR, conversion, retention) with additive + GBM + ES‑RNN stacking and automatic model selection. 100 % Python, CPU‑friendly, explainable.

IST434 Big data analytics end of term paper

Challenge de Data Science da Alura - Alura-Voz

Used Random Forest model to predict customers likely to churn and recommended discount and pricing strategies to improve customers retention.

Data-driven customer churn analysis and predictive modeling using Python

An end-to-end machine learning project predicting bank customer churn with a Gradient Boosting Classifier. It features a complete pipeline for data processing, model training, and real-time predictions via a Flask API. SMOTE is used for handling imbalanced data, and MLflow is integrated for model tracking.

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