Understanding why customers are leaving an online e-commerce company.
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Updated
Jun 7, 2023
Understanding why customers are leaving an online e-commerce company.
This repository contains the implementation of Churn Prediction model on Telco dataset.
ChurnANNalyzer is a customer churn prediction project that utilizes Artificial Neural Network (ANN) algorithm. The project aims to analyze and predict customer churn in a given dataset.
In this project , we aim to perform the data analysis on bank customers data to identify the reasons why customers leave the bank. Tools used for the analysis are Power BI and SQL.
Customer Churn project for a telecom firm. The project aims to predict the possibility of a customer to churn by using methods of Data Analysis and Machine Learning with sound accuracy and justifies its result by showing the expected cost-benefit from following their recommendations.
Explainable customer churn prediction system using XGBoost, SHAP, and FastAPI with calibrated thresholds and ROI-driven retention insights.
Customer churn analysis project using Python, SQL, and Power BI to identify churn drivers, revenue impact, and retention opportunities.
Trying to predict which customers are more likely to churn
Machine learning application that predicts customer churn using the Telco Customer Churn dataset with a Random Forest model and interactive Streamlit dashboard.
By undertaking this project, the company aims to gain valuable insights into customer behavior, enhance service quality, and implement targeted strategies for customer retention and satisfaction. The findings will contribute to informed decision-making and the development of customer-centric business strategies.
End-to-end Customer Churn Prediction & Analytics using SQL, XGBoost, and Streamlit with an interactive dashboard for business insights.
Telecom Customer Churn Analysis using Python, Pandas, Matplotlib and Seaborn. This project explores customer churn patterns and visualizes key factors affecting customer retention in telecom companies.
Customer churn and retention analysis to identify churn patterns, evaluate retention trends, and provide insights to improve customer lifetime value.
TD Bank-Real Time Churn Insights with Robust Machine Learning Models and Interactive Web Deployment
End-to-end MLOps pipeline for predicting customer churn using FastAPI, Docker, Kubernetes, MLflow, and S3
I created a Machine Learning model that can be used to predict customer churn in credit card services.
End-to-end Bank Customer Churn Analysis using Power BI, SQL, Excel, Power Query, and DAX.
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