News

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.
Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data ...
SFU has award-winning research faculty whose interests lie in the interplay between scientific computing, approximation theory, machine learning, the analysis of partial differential equations (PDE) ...
Machine learning is hard.Algorithms in a particular use case often either don't work or don't work well enough, leading to some serious debugging. And finding the perfect algorithm–the set of ...
Machine learning algorithms analyze spending patterns, shopping locations, and transaction timing to detect anything unusual. It’s like having a high-tech firewall constantly scanning and ...
Although most scholars say learning math algorithms like regrouping in addition are essential, some worry that schools don't do enough to support the concepts undergirding these common procedures ...
After a couple of years, I decided to pursue a great interest of mine: understanding the mathematics behind machine learning. I got accepted into the MSc in Mathematics at Queen Mary to pursue that ...
This 30-session course covers a wide variety of topics in machine learning and statistical modeling. The primary goal is to provide participants with the tools and principles needed to solve data ...
The mathematicians, who were working on a machine-learning problem, show that the question of ‘learnability’ — whether an algorithm can extract a pattern from limited data — is linked to a ...
To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the algorithm to recognize those health outcomes.