Software allows scientists to simulate nanodevices on a supercomputer

From computers to smartphones, from smart appliances to the internet itself, the technology we use every day only exists ...
Scientific Research Publishing

Boosting Algorithm: An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ()

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
IEEE

Heart Attack Prediction: A Comparative Analysis of Supervised Machine Learning Algorithms for Early Detection and Risk Stratification

Abstract: Heart attacks are a prominent source of morbidity and mortality globally, demanding the development of precise and efficient predictive models for early identification and risk ...
Scientific Research Publishing

Xie, Z., Jin, J., Liu, D.S., et al. (2024) Construction of a Predictive Model for the Death Risk of Patients with Septic Shock Based on Supervised Machine Learning Algorithms ...

ABSTRACT: Objective: To develop and validate a machine learning-based risk prediction model for postoperative nausea and vomiting (PONV) following gynecological day hysteroscopy, providing ...
GitHub

DR-GEM: Distributionally Robust and latent Group-awarE consensus Machine learning for single cell genomics

DR-GEM is a self-supervised meta-algorithm that combines principles in distributionally robust optimization with balanced consensus machine learning to overcome the challenges of latent class ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
GitHub

ML Algorithm Selector GUI

The ML Algorithm Selector is an interactive desktop application built with Python and Tkinter. It guides users through a decision-making process to identify suitable machine learning algorithms for ...
TechRepublic

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...
techexplorist

A periodic table of machine learning

Caption:MIT researchers created a periodic table of machine learning that shows how more than 20 classical algorithms are connected. The new framework sheds light on how scientists could fuse ...
List of Banks in Belarus

Supervised Learning in Finance

Supervised learning relies on historical, labeled data to train algorithms for specific outcomes. This approach is widely used in the financial sector, where reliable past data can guide future ...