What began as a Ph.D. project has grown into a website with 120,000 unique visitors each year. With the platform OpenML, ...

Due to the need for computing models that can process large quantities of data efficiently and with high throughput in many state-of-the-art machine learning algorithms, the processing-in-memory (PIM) ...

(b) Quantum machine learning in augmenting quantum cryptography. The rest of the article explores the fundamental aspects of quantum cryptography, the role of QML in Quantum cryptography, and three ...

This article explores the top 10 ML algorithms essential for quality assurance, from Decision Trees for defect prediction to Neural Networks for automated test generation, helping test engineers ...

Top Machine Learning Algorithms for HR Analytics Implementing machine learning in HR requires strategic alignment between your organizational needs and algorithmic capabilities. While numerous ...

Machine learning algorithms are the cornerstone of artificial intelligence (AI), enabling computers to learn from data and improve their performance over time without being explicitly programmed.

This project contains machine learning algorithm that makes use of linear regression for predicting weight of the brain based on the size of the head. It also contains regression plot that helps us ...

Look closely at any machine-learning algorithm and you’ll inevitably find people—people making choices about which data to gather and how to weigh it, choices about design and target variables.

We get practical insights into the complexities of machine learning applications, which support the enhanced effectiveness of predictive models in disaster preparedness. The paper not only explains ...