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 ...

Silicon Valley Wants to Build A.I. That Can Improve A.I. on Its Own

Ricursive Intelligence, founded by two former Google researchers and valued at $4 billion, is among several efforts to ...
Analytics Insight

How to Start Your Career as a Machine Learning Engineer: 2026 Guide

Machine learning careers offer strong salary growth across Indian industriesReal projects and deployment skills matter more ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Frontiers

Supervised machine learning approaches for early detection of metabolic and udder health disorders in dairy cows using sensor-derived data

Large Animal Clinic, Veterinary Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania Therefore, it was hypothesized that by analyzing real-time physiological, behavioral, and milk ...
Scientific Research Publishing

Performance of Different Machine Learning Algorithms for Credit Risk Classification ()

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
IEEE

Fault Detection of Three-Phase Controlled Rectifiers Using Supervised Machine Learning Algorithms

Abstract: Power converters are integral to modern power systems and industrial applications, facilitating efficient and reliable energy transfer between sources and loads. However, their widespread ...
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

Sen, P.C., Hajra, M. and Ghosh, M. (2019) Supervised Classification Algorithms in Machine Learning: A Survey and Review. In: Mandal, J.K. and Bhattacharya, D., Eds., Emerging ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...
Frontiers

Machine-learning algorithm to predict home delivery after antenatal care visit among reproductive age women in East Africa

Background: Maternal and child health remains a global public health issue, particularly in low- and middle-income countries where maternal and child mortality are extremely high. The World Health ...
BizTech

What Are the Benefits of Unsupervised Machine Learning and Clustering?

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...