Trabajo de Fin de Máster KSchool

Using binary models (logistic and probit) to analyze risk factors associated with type 2 diabetes based on BRFSS 2015 data. The study identifies key factors such as obesity, age, physical activity, and socioeconomic status.

**Intro to Statistics**: Discover the fascinating world of statistics with this engaging and accessible guide. Perfect for beginners, this book covers everything from p-values and t-tests to machine-learning models like random forests. Learn through practical examples and R code snippets, and unlock the power of statistical analysis.

Binary Classification Usinig 6 Machine Learning Tools, R, and Rmarkdown by Matt Curcio

Este projeto tem como objetivo, através de uma regressão binomial do tipo logito, predizer as chances de um nódulo de mama ser maligno ou benigno. O projeto visa aplicar o aprendizado das aulas do programa de Especialização em Data Science e Big Data da UFPR e compor parte da nota na disciplina de Inferência Estatística parte 3.

Modelo predictivo de clasificación de fraudes financieros como proyecto final de Análitica de Negocios en ESEN.

Project for the Machine Learning 2021/22 class at the Faculty of Economic Sciences, University of Warsaw. I was responsible for the drug abuse prediction task for which I build logit, probit, KNN and SVM classification models.

Calibration programs in Excel for the laboratory

Additional R scripts to produce data analysis and wrangling. You will need to run the main file here to get the manipulated dataframe that I use in the hbc-ctol repository. Here, some analysis that I did initially can also be found. The complete development environment for the stuff that you see on RPubs is also here. In memory of the late Jorge…