Predicting Airline Delays at Scale with Spark ML

A UC Berkeley team used Apache Spark ML to predict airline delays at scale, training models on millions of flight records and ...
The New York Times

In N.Y.C. Classes, Teachers Can Use A.I. to Plan but Not to Assign Grades

The largest school system in the United States released its first guide on how teachers can incorporate artificial intelligence into their work and schools. By Matthew Haag In New York City schools, ...
Hosted on MSN

World of Warcraft update is making changes to multiple classes

This article was updated by Andrea Trama on March 18, 2026, with reference to the classes' performance in M+ Dungeons after the update. It was first published on March 15. Ahead of World of Warcraft: ...
NPR

A college student's perspective on using AI in class

[Maximilian Milovidov is a freshman at Columbia University and a member of TikTok's Youth Council. He used a large language model to edit this essay for length and a human to edit for content. This ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Hosted on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Gizmodo

This Professor Let Half His Class Use AI. Here’s What Happened

To use artificial intelligence, or not to use AI? That is the question that all students and their educators face in today’s age. While people have been endlessly arguing the pros and cons of ...
IEEE

Multi-Class Classification of BMI Categories with Logistic Regression, SVM, Random Forest, and XGBoost

Abstract: Body Mass Index is a main indicator for assessing weight related health risks and classifying individuals listed as underweight, normal, overweight or obese. Accurate prediction of BMI ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...