This project demonstrates a data product focused on Natural Language Processing. The application predicts the most likely next word in an English phrase based on a simple statistical language model. The model uses cleaned text data to create bigram frequency tables and returns the most probable next word for user input. The goal is to provide a fast, interactive prototype that showcases how predictive text systems are designed.

Melakukan analisis PCA dari data Employee Attrition

Matemáticas Aplicadas a la Empresa y Negocios

Fort Collins Student data collection report

The purpose of this project is to predict whether a patient has heart disease or not, based on clinical and demographic variables. We used the Cleveland Heart Disease dataset and compared three models: a logistic regression, a cost-sensitive decision tree and a random forest. Our goal is to evaluate model performance and see which approach is most reliable for this classification task.

Analysis with data from 2 subjects recruited from Prolific. Note that correlation tables could not be produced because psych::corr.test requires at least 3 subjects to compute confidence intervals

Ejercicio de modelos predictivos con regresión lineal simple.