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The goal of this project is to build a machine learning model to predict customer churn for Camtel 📡, a major telecommunications provider. Customer churn—the rate at which customers leave the service—is a key challenge that directly impacts revenue 💸 and business stability 🏢.
Developed a sentiment analysis model to measure tweet positivity across regions using advanced NLP techniques. This project involved data preprocessing, feature engineering with TF-IDF and Doc2Vec, and training supervised machine learning models. Performance was validated using cross-validation and metrics like accuracy and precision