Automatic Korean word spacing with R

R Interface to Open Neural Network Exchange (ONNX)

Unsupervised Deep Architechtures in R

OmicSelector - Environment, docker-based application and R package for biomarker signiture selection (feature selection) & deep learning diagnostic tool development from high-throughput high-throughput omics experiments and other multidimensional datasets. Initially developed for miRNA-seq, RNA-seq and qPCR.

Showcase for using R + MXNET along with AWS and bitfusion for deep learning.

Applying Deep Machine Learning for psycho-demographic profiling of Internet users using O.C.E.A.N. model of personality.

Time series with torch

R package for automatic hyper parameter tuning and ensembles with deep learning, gradient boosting machines, and random forests. Powered by h2o.

Improved Mortality Forecasts using Artificial Intelligence.

Replication code for "RNN-based counterfactual prediction, with an application to homestead policy and public schooling"

Repository for Udemy Course: Identify problems with Artificial Intelligence

The integration of machine learning and methodologies like deep learning will help greatly in classification of blood cells. Here i have implemented the deep learning model run with optimized hyperparameters against the other machine language methodologies like SVM and deep learning with defaults.The dataset for this project was taken from the K…

Projects and Certificates of my Google-Career-Certificates on Coursera

An R package which provides a a neural network framework based on Generalized Additive Models

Analysis of simulated genotype alignment data for use in CNN estimators (Johnson and Wilke, 2022)

deep learning patient classifier based on patient similarity networks

Elman Deep Neural Network in Forecasting application using R programming tested on 3 types of dataset

Flexible deep learning neural network. Implements a multi layer perceptron and autoencoders.

Web-application for 2D NMR peak picking and result visualisation using a Laplacian of Gaussian (LoG) and deep learning (TF Keras) approach - currently under development

A classifier written in R which predicts whether a patient, diagnosed with "Hepatocellular Carcinoma", is likely to live or die within a year