Business Model

Performing Artificial Neural Networks (ANN) to classify malignant and benign tumors in breast cancer patients.

Using machine learning techniques with Kepler Space Telescope exoplanet search data to train and tune classification models

This R Notebook project illustrates how Artificial Neural Network can be applied to Reservoir Characterization dataset. It illustrates the relationship between a dependent variable and several independent variables using ANN.

An ANN model is created for identification of the best kind of concrete used in infrastructure industry.

Mi TFM titulado "Aplicación de redes neuronales artificiales y programación cuadrática en la gestión de carteras"

Course work related to the Certification in Practice of Data Analytics (CDPA) offered by the Ohio State University

Dashboard de mi TFM titulado "Aplicación de redes neuronales artificiales y programación cuadrática en la gestión de carteras"

Examine the accuracy of match outcome prediction solely based on hero selection

Proof-of-concept R codes: XOR neural network, circle packing algorithm, real-time graphing, Monte Carlo simulation

Artifial nural networks (script and example files)

Portfolio Optimization with Feedback Strategies Based on Artificial Neural Networks

Learn R Programming Language for Statistics & Data Science

Presentación de mi TFM titulado "Aplicación de redes neuronales artificiales y programación cuadrática en la gestión de carteras"

Aplicações em R para previsão de séries temporais utilizando modelagem Neural Network Autoregressive (feed-forward)

This is the repository for CKME136 Ryerson Big Data Certificate

Self-Organizing Maps(SOM) or self-organizing feature map (SOFM) is a type of artificial neural network (ANN) that is trained using unsupervised learning. Using R.

Artificial Neural Networks for Irrigation (ANNI): predicting available water capacity (AWC) to optimize irrigation scheduling in vegetable production. Combines MLP, LSTM, and ensemble models with explainable AI techniques.

Research Project in the area of ​​Deep Learning applied to credit risk. This model achieved better results compared to other published papers. This project is focused on the Fintech industry.

Artificial Neural Networks with R using keras, neuralnet and functional API.