Scientific American

‘Small Data’ Are Also Crucial for Machine Learning

When people hear “artificial intelligence,” many envision “big data.” There’s a reason for that: some of the most prominent AI breakthroughs in the past decade have relied on enormous data sets. Image ...
Drexel University

Drexel WiCS Presents: Algorithmic Statistics for Machine Learning

Join the Drexel Women in Computing Society (WiCS) for a talk with Electrical and Computer Engineering Associate Professor Andrew Cohen, PhD on the use of Kolmogorov complexity and algorithmic ...
Forbes

The Five Major Platforms For Machine Learning Model Development

Over the past two decades, the biggest evolution of Artificial Intelligence has been the maturation of deep learning as an approach for machine learning, the expansion of big data and the knowledge of ...
Analytics Insight

10 Most Common Machine Learning Mistakes and Tips to Fix Them

Overview: Machine learning failures usually start before modeling, with poor data understanding and preparation.Clean data, ...
Quanta Magazine

What Is Machine Learning?

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 ...
Drexel University

Master’s (MS) in Machine Learning and Artificial Intelligence

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) ...