How much math knowledge do you need for machine learning and deep learning? Some people say not much. Others say a lot. Both are correct, depending on what you want to achieve. There are plenty of ...

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 ...

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 ...

Citation: Ha NT, Manley-Harris M, Pham TD, Hawes I. A Comparative Assessment of Ensemble-Based Machine Learning and Maximum Likelihood Methods for Mapping Seagrass ...

What are the differences between econometrics, statistics, and machine learning? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better ...

Recruiting machine learning (ML) talent is different than for traditional software development. The field of artificial intelligence is so young that it can be difficult to parse candidates by their ...

The groundwork for machine learning was laid down in the middle of last century. But increasingly powerful computers – harnessed to algorithms refined over the past decade – are driving an explosion ...