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