LLM-Powered Churn Risk Analyzer for Scalable 2026 Decision Support
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)
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.
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).
Churn analysis library
Analyzing customer attrition & strategies to reduce churn via AutoML techniques & PowerBI
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.
Unified ML platform serving two production risk models behind one API, fraud detection using a Logistic Regression pipeline at 92.4 percent accuracy and 0.90 F1, and churn prediction using a five-estimator hard-voting ensemble at 85.6 percent accuracy, with SMOTE balancing, sub-0.5 second inference, and CI-enforced 90 percent test coverage.
This repository contains a curated collection of intermediate-level projects showcasing skills in data cleaning, analysis, visualization, and business insights.
A production-style event analytics system focused on immutable event modeling, SQL-driven metrics, retention, and funnel analysis.
Churn Analyzer: Analyze and understand user churn rate in your PostgreSQL database effortlessly.
Curso de Deep Learning con Tensorflow + Keras
Customer Churn Analysis for a website
Application pour analyser et prédire le churn client avec visualisations interactives
A project demonstrating how to predict customer churn based on product usage behaviours.
visualisation of churn data of a bank
Command line tool to generate actionable metrics for priorizing refactors on your rust project
High-performance code risk telemetry engine for structural hotspot analysis. Correlates AST-based complexity metrics with Git churn signals to identify volatile, high-risk code regions.
Banks lose customers silently. Without a model, the retention team has no idea who is about to leave until it is too late. Goal: flag at-risk customers early enough to act. Built a full ML pipeline on 10K customers. Result: 83% Recall, meaning 8 out of 10 churners identified before they leave, giving the retention team an actionable list.
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