Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and ...

Machine learning holds promise for optimizing treatment strategies and potentially improving outcomes in respiratory failure ...

The accurate estimation of bearing stratum depth, the subsurface soil or rock layer depth that can support a foundation, is ...

Blasting is considered an indispensable process in mining excavation operations. Generally, only a small percentage of the total energy of blasting is consumed in the fragmentation and displacement of ...

Pairs Trading Strategy with Machine Learning (KNN) This project implements a pairs trading strategy integrated with machine learning using the K-Nearest Neighbors (KNN) algorithm. Developed as part of ...

As mentioned above, several studies have addressed both detection and localization of brain lesion using microwave data through a single machine learning algorithm. Apart from a recent study [20], the ...

A machine learning algorithm based on the complete set of features was used to classify the main tree species in the study, which achieved a high classification accuracy, with an OA higher than 90%.

🐦 Tweet Classification with Machine Learning This project focuses on classifying tweets using various supervised machine learning algorithms. It leverages natural language processing (NLP) techniques ...

The K-Nearest Neighbors (kNN) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of traditional kNN ...

Machine learning methods for land use and land cover (LULC) classification are vital for monitoring environmental changes. Remote sensing advancements increase the potential for classifying land cover ...