Science Is Drowning in AI Slop

Now they’re being clogged with AI slop. Scientific publishing has always had its plumbing problems. Even before ChatGPT, ...

This OS quietly powers all AI - and most future IT jobs, too

Modern AI began with open source, and it ran on Linux. Today, Linux isn't just important for artificial intelligence; it's the foundation upon which today's entire modern AI stack runs. From ...
Frontiers

Efficiency algorithm: new AI-based tools for an adaptive learning environment

Introduction: The learning process is characterized by its variability rather than linearity, as individuals differ in how they receive, process, and store information. In traditional learning, taking ...
GitHub

Salary_prediction using Linear_Regression

This is a machine learning-based web application built with Flask that predicts the estimated salary of an individual based on their: Years of Experience Education Level Location Previous Salary The ...
Science Daily

Machine learning algorithm brings long-read sequencing to the clinic

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...
Frontiers

Advances in machine learning for the detection and characterization of microplastics in the environment

1 Department of Environmental Sciences, Jahangirnagar University, Dhaka, Bangladesh 2 Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden ...
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Linear Regression Cost Function | Machine Learning | Explained Simply

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...
IEEE

Systematic Bias of Machine Learning Regression Models and Correction

Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large-valued ...