Learn how to implement backpropagation using automatic differentiation from the ground up in Python—no libraries, just pure ...

We are currently looking for a Research Intern to join the team in Delft to work on Machine Learning Models for Hyperspectral Data to start in September 2025 . Are you ready to make an impact within S ...

Budoen, A.T., Zhang, M.W. and Edwards Jr., L.Z. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, ...

Abstract: Generating intuitions from data using data mining and machine learning algorithms to predict outcomes is useful area of computing. The application area of data mining techniques and machine ...

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! Donald Trump blasts Putin ...

Hand-Gesture-2-Robot is an image classification vision-language encoder model fine-tuned from google/siglip2-base-patch16-224 for a single-label classification task. It is designed to recognize hand ...

The Part algorithm (Recursive Partitioning and Regression Trees), implementing the CART (Classification and Regression Trees) technique, was used for this purpose. The Gini index, which maximizes ...

GLOBAL_HEALTH_ANALYSIS is a comprehensive tool designed to evaluate health trends across different regions. It uses data visualization to highlight key health indicators, enabling users to identify ...

The accuracy of multivariate time series classification algorithms is critical for the effective recognition of human activities by wearable devices, timely detection, and warning of road or component ...

Extracted features can be optimized using some optimization algorithms and then be fused together. Feature fusion greatly impacts the overall classification accuracy. The subsequent section presents ...