Detect fraudulent job postings via Kaggle dataset using classical ML + text features.

GAMM and ANN modelling for Viral Abundance Time Series

An R-package to estimate average causal effects with AIPW using Deep Neural Networks, in particular Convolutional NN.

Different approaches to solve MNIST problem with convolutional neural networks

📑 Solution manual for the text book Neural Network Design 2nd Edition by Martin T. Hagan, Howard B. Demuth, Mark Hudson Beale, and Orlando De Jesus

Randomized and quasi-randomized nnetworks for supervised learning and multivariate time series forecasting

All of my R code from the Deep Learning & AI IV module at Durham University

Code and analysis pipeline for the paper "Genomic Prediction through Machine Learning and Neural Networks for Traits with Epistasis" (Comput Struct Biotechnol J, 2022).

Boosted Configuration (Neural) Networks

Advanced Customer Segmentation methods in R

R Script for AI Image and Location Recognition that can also generate an automated prompt for AI text-generation of a social media post.

Proyectos de la materia Programación 3 - Instituto ORT

Academic portfolio which showcases projects completed during my graduate studies

Here is a collection of machine learning methods implemented from scratch.

All the Data Science projects I've done, during the course, or after.

This project is a classification problem with a response variable to classify handwritten images as the numbers, 'one', 'seven' or 'eight. This is a classification problem using the Cross Entropy loss function, the 'tanh' activation function using h2o deeplearning as well as Trees.

Bankruptcy prediction - LDA, logit, NN

Parts of code from my MSc. dissertation project. Uses yahoo API to load past stock data for training and backtesting various traditional and experimental models for VaR calculation. Written in R & Python.

R course