Neel Somani has built a career that sits at the intersection of theory and practice. His work spans formal methods, mac ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

Supervised machine learning uses labeled data to teach algorithms pattern recognition. It improves prediction accuracy in industries like finance and healthcare. Investors can gauge a company's ...

Over the last several decades, urban planners and municipalities have sought to identify and better manage the socioeconomic dynamics associated with rapid development in established neighborhoods.

If you’re a data scientist or you work with machine learning (ML) models, you have tools to label data, technology environments to train models, and a fundamental understanding of MLops and modelops.

Reinforcement learning algorithms help AI reach goals by rewarding desirable actions. Real-world applications, like healthcare, can benefit from reinforcement learning's adaptability. Initial setup ...

Who is the Master's in Artificial Intelligence and Machine Learning program for? Drexel’s College of Computing & Informatics' Master of Science in Artificial Intelligence and Machine Learning (MSAIML) ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...