The Fashion-MNIST dataset and machine learning models.

Using R and machine learning to build a classifier that can detect credit card fraudulent transactions.

Solutions and code examples from An Introduction to Statistical Learning (Second Edition) by James, Witten, Hastie, and Tibshirani.

This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.

This project provides a series of MxNetR example for letting readers to get started quickly.

Rainfall prediction from Australian weather dataset using multiple machine learning models.

Fuzzy Clustering Using Hybrid Fuzzy c-means and Fuzzy Particle Swarm Optimization (A Research Paper Implementation along with Self-organization feature map (SOFM) implementation)

Using machine learning algorithms like support vector machines, artificial neural networks and random forest to predict airline customers satisfaction

Full machine learning practical with R.

2016 General Election, A Geographic and Demographic Analysis - Using Data Visualization and Machine Learning in R to study and model 2012 and 2016 general election voting patterns

This article introduces artificial neural networks as a computational tool to utilize legacy archaeological data for precisely and accurately estimating dates of residential site occupation. The implementation of this deep learning algorithm can provide high-resolution demographic reconstructions of a study area from non-collection, non-invasive…

Functions for processing and analyzing metabolomics data

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.

Detect Credit Card Fraud with Machine Learning in R

Performs OCR on the MNIST dataset. From my BSc. AI & Robotics at Prifysgol Aberystwyth

Applied several ML Algorithms

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