We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

Researchers Yue Zhao and Kang Pu from Stony Brook University—in collaboration with Ecosuite's John Gorman and Philip Court, ...

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

What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.

Arkham has unveiled its most extensive privacy-network mapping effort to date. The firm added full Zcash on-chain tracking, which now marks more than 53 percent of all ZEC transactions. Moreover, the ...

MIT researchers have developed a method that generates more accurate uncertainty measures for certain types of estimation.

International humanitarian aid organizations rely on analyses from the Integrated Food Security Phase Classification (IPC) ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...

Mathbots haven’t done much for K-12 math instruction. Can more sophisticated uses of AI succeed in turning around American students’ falling scores?

The future of hiring may utilize AI, but it is also accountable, auditable and, increasingly by law, must include ...