## R Packages

- fastknn: Fast k-Nearest Neighbor Classifier for Large Datasets.
- elmnet: Regularized and Pruned Extreme Learning Machines in R.
- impcov: Improved Covariance Matrix Estimators in R. (
**in development**)

## Tutorials

- Feature Engineering: Using Feature Engineering to improve Model Prediction performance (
*in Portuguese*). - Intro to Kaggle: Deliberate Practice and Kaggle Datasets (
*in Portuguese*). - EDA with R: Exploratory Data Analysis with R (
*in Portuguese*). - Data Science Roadmap: How to start with Machine Learning and Data Science in
**Python**and**R**(*in Portuguese*). - H2O.ai Tutorial: H2O Tuning and Ensembling Tutorial for R.

## R Shiny Applications

- Pruned Extreme Learning Machine: measuring neuron importance with the F-score measure on SLFNs trained by the ELM algorithm, and eliminating the non-important ones to avoid overfitting.

## Machine Learning Animations

- Gradient Boosting Machine.
- K-Nearest Neighbors Classifier.
- EM Algorithm.
- Gaussian Mixture Density.
- Regularized ELM.
- K-Means Clustering.
- Principal Components Analysis.

## Master’s Thesis

My Master’s thesis on **Bayesian Classification with Regularized Gaussian Models**: Master’s Thesis.