Abstract: The Support Vector Machine (SVM) performance is highly dependent on the selection of optimal hyperparameterse Conventional optimisation methods, including grid search, gradient descent, ...

Either way, let’s not be in denial about it. Credit...Illustration by Christoph Niemann Supported by By Kevin Roose and Casey Newton Kevin Roose and Casey Newton are the hosts of The Times’s “Hard ...

1 Faculty of Mathematics and Computer Science,, Felix Houphouët-Boigny University, Abidjan, Côte d’Ivoire. 2 Institute for Mathematical Research (IRMA), Abidjan, Côte d’Ivoire. 3 Higher Teacher ...

This project explores the mathematical and practical implementation of Support Vector Machines (SVMs) optimized using Stochastic Gradient Descent (SGD). It includes a theoretical foundation, algorithm ...

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...

The widespread adoption of AI is creating a paradigm shift in the software engineering world. Python has quickly become the programming language of choice for AI development due to its usability, ...

An experimental ‘no-GIL’ build mode in Python 3.13 disables the Global Interpreter Lock to enable true parallel execution in Python. Here’s where to start. The single biggest new feature in Python ...

The sale will feature 50,000 Hyperfuse nodes across 20 pricing tiers. Node sales are a growing fundraising method in blockchain. The sale follows a successful $12 million Series A fundraising round ...

Early diagnosis of pneumonia is crucial to increase the chances of survival and reduce the recovery time of the patient. Chest X-ray images, the most widely used method in practice, are challenging to ...