From Text To Tables: Why Structured Data Is AI’s Next $600B Frontier

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
IEEE

Enhanced Classification of Migraine Headaches: Leveraging Machine Learning, Deep Learning, and Bayesian Networks with Data Augmentation

Abstract: This study addresses the classification of migraine headaches using advanced machine learning techniques, specifically ensemble models and boosting methods. We employed data augmentation to ...
TheServerSide

Google Machine Learning Certification Sample Questions

Community driven content discussing all aspects of software development from DevOps to design patterns. The Google Cloud Professional Machine Learning Engineer certification validates your ability to ...
TheServerSide

Sample Questions for AWS' Machine Learning Associate Certification

Community driven content discussing all aspects of software development from DevOps to design patterns. The AWS Machine Learning Associate certification validates your ability to configure, build, and ...
The New York Times

A Trump Administration Playbook: No Data, No Problem

A pattern of getting rid of statistics has emerged that echoes the president’s first term, when he suggested if the nation stopped testing for Covid, it would have few cases. The NOAA Center for ...
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 ...
Frontiers

Heterogeneous transfer learning model for improving the classification performance of fNIRS signals in motor imagery among cross-subject stroke patients

Introduction: Motor imagery functional near-infrared spectroscopy (MI-fNIRS) offers precise monitoring of neural activity in stroke rehabilitation, yet accurate cross-subject classification remains ...