Andres R.

Parte de la generación °10 del programa Ingenia, el cual cuenta con actividades, y eventos propios del mismo que involucran a todas las empresas del grupo con el objetivo de formar a la siguiente generación de lideres empresariales. - Al programa ingresa una promoción de +30 ingenias. Selectividad del 5% en el proceso de selección.

Focus on the implementation and testing of machine learning models for forecasting and demand prediction. • Advanced time series analysis: Evaluation of seasonality (additive and multiplicative), trend analysis, residuals, autocorrelation, partial autocorrelation, feature engineering, visualization, and imputation of missing data. • Predictive model evaluation: Testing of advanced models such as LSTM, VanillaTransformer, TimeMixer, AutoARIMA, CatBoost, LightGBM, and XGBoost. • Pipeline development: Implementation of a pipeline in FastAPI for the evaluation and testing of time series models. • Containerization and deployment: Dockerization of the application and deployment on AWS EC2, ensuring scalability and system availability.

I designed prompts to guide different AI LLM models in generating code, followed by compilation and testing. Unit test classes were developed to evaluate the functionality of the results generated by each model.