Abstract: This review article provides a thorough assessment of modern and innovative algorithms for text classification through both observational and experimental evaluations. We propose a new ...

Social media and algorithmic recommendations aren’t just reflecting our divisions — they’re driving them. According to a poll conducted by Siena University and The New York Times, “most voters think ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...

Spotware, the developer of the cTrader multi-asset trading platform has launched an essential update with the introduction of cTrader Windows version 5.4, native Python, supporting algorithmic trading ...

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 ...

Learn how the Adadelta optimization algorithm really works by coding it from the ground up in Python. Perfect for ML enthusiasts who want to go beyond the black box! Florida State Bracing for Hefty ...

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 ...

Objective: This study aimed to determine the diagnostic precision of a deep learning algorithm for the classificaiton of non-contrast brain CT reports. Methods: A total of 1,861 non-contrast brain CT ...

Heart disease classification using machine learning algorithms with hyperparameter tuning for optimized model performance. Algorithms include XGBoost, Random Forest, Logistic Regression, and moreto ...