Typescript library to access Faraday's API infrastructure for B2C predictions

Analyze IBM Telco Customer data to offer valuable insights for data-driven decision-making on customer retention to reduce churn

This project was the outcome of the Corporate Reseach Project as a part of Masters in Data Sciences and Business Analytics program at ESSEC-CentraleSupelec and monitored by Deloitte. In this study, we propose and evaluate a predictive model for employee churn using machine learning techniques.

A deep learning model for churn prediction in subscription services based on user events, usage momentum and behaviour.

A telecom company wants to find out the likelihood of a customer leaving the company. This is a classification model that predicts if a customer will churn or not.

Power BI Dashboards and Power Point Presentations

📊 This project focuses on customer churn analysis and prediction in the telecommunications sector. Using data analysis, modeling, and predictive techniques, it aims to understand and mitigate customer loss by developing strategies.

Data Science Challenge from Coursera Project : Churn Prediction

Repositori ini berisi proyek data mining yang menganalisis perilaku pelanggan di sektor perbankan, dengan fokus pada prediksi churn. Dilengkapi dengan visualisasi data dan implementasi algoritma Naive Bayes untuk analisis lebih lanjut.

The app utilizes a machine learning model trained on customer data to predict the likelihood of a customer leaving the bank based on various features such as credit score, age, account balance, and more.

A webapp to predict Churn against customers and employees, along with feature for data visualization

predictive models that can forecast the likelihood of churn for individual customers

Developed a desktop application, that uses ML algorithms to accurately predict customer churn based on customer details. The application helps to identify customers at risk of churning using regression models.

This project develops a machine learning model to predict customer churn for a California-based telecom company using data from 7043 customers. Our goal is to enhance customer retention strategies through detailed data analysis and feature engineering.

Customer Churn Prediction WIth ANN model by Tensorflow

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.

A Streamlit app to predict Telecom Churn