The race to make large language models faster and cheaper to run has largely been fought at two levels: the model architecture and the hardware. But there is a third, often underappreciated frontier — ...

ABSTRACT: Automatic detection of cognitive distortions from short written text could support large-scale mental-health screening and digital cognitive-behavioural therapy (CBT). Many recent approaches ...

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...

This repository contains two powerful Python scripts for spam classification using Naïve Bayes and Support Vector Machine (SVM) algorithms. Each script implements a complete pipeline for loading, ...

Abstract: Performance evaluation of the linear kernel SVM for land cover classification using the GEE platform in Telangana, India (Longitude: 79.78E Latitude: 7.78N) is presented in this paper.

Support vector machines (SVMs) constitute a class of supervised learning models designed to perform classification by constructing a decision boundary, or hyperplane, that optimally separates data ...

Implementation of a Simple Perceptron (Simplest Neural network by Frank Rosenblatt) in C based on the example given example in the Veritasium video.