Abstract: This study addresses the lack of comprehensive evaluations of feature scaling by systematically assessing 12 techniques, including less common methods such as VAST and Pareto, in 14 machine ...

Abstract: In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement ...

Meta released an open source language learning app for Quest 3 that combines mixed reality passthrough and AI-powered object recognition. Called Spatial Lingo: Language Practice, the app not only aims ...

Karen Roehr-Brackin received funding from the British Academy/Leverhulme Trust (grant reference SRG23\230787) which supported the research project reported here. If you’ve always wanted to learn a new ...

Community driven content discussing all aspects of software development from DevOps to design patterns. This exam measures your ability to apply machine learning knowledge in the AWS environment. It ...

Predicting performance for large-scale industrial systems—like Google’s Borg compute clusters—has traditionally required extensive domain-specific feature engineering and tabular data representations, ...

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...

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 ...

This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning. This ...

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 ...