Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.

Programa Computarizado, elaborado en el lenguaje de programacion MATLAB, referente al Trabajo Especial de Grado para optar al Título de Ingeniero Industrial, en la Facultad de Ingeniería de la Universidad de Carabobo, año 2015; la cual fue reconocida con mención honorífica.

A Python Package to Create Synthetic Tabular Data

Multivariate independent comparison of observations.

Additional univariate and multivariate distributions

Implemented from scratch a sampling method to draw samples from a multivariate Normal (MVN) distribution in JAX.

Collection of missing multivariate random number distributions for Modern C++ with STL-like API.

Provides multivariate normal distribution sampling and matrix inversion for Jetbrain's new NDArray library Multik, by bodging it with some classes (including tests) from Apache Commons Maths 3 & 4, translated into Kotlin and made JVM independent for a Kotlin Multi-Platform project.

Implementation of the Extreme Joint Distribution algorithm in C++

Lottery analysis

Here all my machine learning notebooks will be uploaded

Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.

Robust estimation using heavy-tailed distributions

A Collection of Basic Utilities for Statistical Analyses

A simple utility to perform sampling from multivariate distributions (supported by a PyTorch backend)

Multivariate independent comparison of observations

Machine Learning algorithms using Sklearn and Scikit python libraries for comparing their behaviour on anomaly detection

An object-oriented approach to implement anomaly detection in Python using semi-supervised learning

UniBG modelli stocastici prova 00 a.a. 2017-2018

Random data generator from scratch. (Using numpy for simple mathematical functions only)