Leveraging Machine Learning to Unveil the Critical Role of Geographic Factors in COVID-19 Mortality in Mexico

This paper presents a web-based intelligent analytics system that integrates automated data ingestion, preprocessing, distributional analysis, algorithm recommendation, and model execution within a user-friendly interface. The platform supports common data formats and guides users through statistical checks such as normality tests, ANOVA, and correlation diagnostics, ensuring analytical rigor. It incorporates machine learning techniques including KMeans, SVM, and regression models, automatically recommending appropriate methods based on dataset characteristics. A key innovation is the seamless integration of statistical assumption validation with ML workflows, enabling users without technical expertise to perform reproducible analyses. We demonstrate applicability on COVID-19 datasets and financial time series, highlighting its utility in real-world data science scenarios.