Justdial on MSN

Understanding the types of machine learning and their power in AI

Explore the Types of Machine Learning and their impact on AI. Learn how these core frameworks drive digital innovation and ...
The Province on MSN

Canucks Coffee: Big data in hockey, plus the Guenther return

I chuckled a little when hearing declarations that NHL teams are looking more and more toward AI.
Tech Xplore

Living brain cells enable machine learning computations

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...
IEEE

FedGDS: Federated Semi-Supervised Learning Algorithm Based on Evidence Theory and Graph Convolution

Abstract: Traditional deep learning methods have achieved remarkable success by leveraging large-scale labeled datasets. However, in real-world applications, acquiring labeled data is often expensive, ...
GitHub

What is Unsupervised Learning?

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
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 ...
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 ...