Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

The recursive Gaussian process regression (RGPR) is a popular calibrating method to make the developed soft sensor adapt to the new working condition. Most of existing RGPR models are on the ...

With excellent representation power for complex data, deep neural networks (DNNs) based approaches are state-of-the-art for ordinal regression problem which aims to classify instances into ordinal ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire ...

machine-learning deep-learning semi-supervised-learning drug-discovery kernel-methods transcriptomics genomic-selection biological-networks high-dimensional epigenomics prototype-pattern ...

This repository contains code and resources related to the scientific paper titled "Tailored Architectures for Time Series Forecasting: Evaluating Deep Learning Models on Gaussian Process-Generated ...