Challenge Telecom X Parte 2 - análisis de datos
Analyze Telco customer data to predict customer churn using Logistic Regression, Decision Tree, Random Forest, and XGBoost. Includes data preprocessing, EDA, feature engineering, and model evaluation.
Python-based CDR forensic analysis dashboard for telecom communication analysis, suspicious activity detection, and visualization using Flask.
Statistical analysis of consumer behavior for Megaline's prepaid plans. Performed hypothesis testing (t-tests), multi-source data merging, and revenue modeling to determine plan profitability and regional market differences.
Customer Churn Analysis using Python | EDA | Data Visualization | Business Insights
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