This project is targeting people who want to learn internals of ml algorithms or implement them from scratch. The code is much easier to follow than the optimized libraries and easier to play with.

Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Endoscopy-based deep learning algorithms achieve higher sensitivity, specificity, and overall diagnostic accuracy than endoscopists for early ESCC detection.

Governments use algorithms to select, advise or profile citizens, and to assess risks. But how do you know whether such an ...

Modern air defense confrontations demand rapid, precise task assignments in environments where threats evolve within seconds.

A new algorithm could drive breakthroughs in understanding cancer, Alzheimer's disease and other potentially fatal conditions ...

Time for a gut check. Cases of colorectal cancer are on the rise, surpassing breast and brain cancer as the leading cause of ...

Arguing that AI has evolved beyond just a specialization within computer science studies, Syracuse University will launch ...

Every AI model depends on labeled data. Data annotation is the process of tagging images, text, audio, or video so that ...

Abstract: Malware has emerged as a cyber security threat that continuously changes to target computer systems, smart devices, and extensive networks with the development of information technologies.

Abstract: Multi-label learning studies the problem where each example is represented by a single instance while associated with a set of labels simultaneously. During the past decade, significant ...

Built on top of the cudamat library by Vlad Mnih and cuda-convnet library by Alex Krizhevsky.