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1. player_churn_prediction player_churn_prediction Public

   Predicting player churn in online games using XGBoost: 99% accuracy, 91% recall. Includes business context and retention strategy.

   Jupyter Notebook 1

2. airbnb-data-cleaning-and-eda airbnb-data-cleaning-and-eda Public

   EDA and data cleaning on Airbnb listings in Rio de Janeiro, pricing factors, outlier removal, feature encoding.

   Jupyter Notebook

3. customer-churn-prediction customer-churn-prediction Public

   End-to-end churn prediction pipeline with modular /src architectur, data processing, model training and evaluation.

   Python

4. Clusteriza-o_-RFV_-Segmenta-o_Clientes Clusteriza-o_-RFV_-Segmenta-o_Clientes Public

   E-commerce customer segmentation using RFM (Recency, Frequency, Monetary) analysis and K-Means clustering to drive targeted CRM, customer loyalty, and retention strategies.

   Jupyter Notebook

5. modelo_regressao modelo_regressao Public

   Supervised regression model to predict retail product prices based on user ratings, product categories, and discounts. Benchmarking Linear Regression, Random Forest, and XGBoost.

   Jupyter Notebook

6. powerbi-dashboards powerbi-dashboards Public

   Interactive Power BI dashboard for e-commerce sales analysis, revenue trends, customer segmentation and channel performance.

   HTML