This workshop will consider several applications based on machine learning classification and the training of artificial neural networks and deep learning.

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

RPG Larian's head writer has a simple answer for how AI-generated text helps development: 'It doesn't,' thanks to its best output being 'a 3/10 at best' worse than his worst drafts Graphics Cards 'It ...

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

NFL Week 1 concludes with a Monday Night Football matchup at 8:15 p.m. ET between the Chicago Bears and Minnesota Vikings (-1, 43.5). Quarterback J.J. McCarthy will make his regular season debut after ...

The 2025 NFL season kicks off tonight with a key NFC East matchup between the Dallas Cowboys and the defending Super Bowl champion Philadelphia Eagles (-8, 47.5). Since 2010, Dallas and Philadelphia ...

This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...