A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

David Gerbing from the School of Business at Portland State University introduces lessR, a tool designed to facilitate professional-quality data visualizations and data analysis without programming re ...

The Sports Analytics Research Group employs quantitative analysis to give teams the hard numbers they need to perform better ...

EncryptPro handles the basics of encrypting your important files at no charge, while a subscription gets you enhanced features and convenience. It’s a bit rough around the edges, but it shows great ...

Here's what that shift to AI means for the recruitment process, and how you can ensure your application gets picked from the ...

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Moreover, our pipeline is highly data driven, enhancing study data with a rich variety of publicly available information and knowledge sources. We also showcase our pipeline and provide guidance on ...

Abstract: Deep-learning (DL) algorithms, which learn the representative and discriminative features in a hierarchical manner from the data, have recently become a hotspot in the machine-learning area ...

Retention analysts say Shorts older than 28-30 days are being deprioritized in recommendations. The reported shift affects channels ranging from 100 million to one billion monthly views. Creators warn ...

Kats is a toolkit to analyze time series data, a lightweight, easy-to-use, and generalizable framework to perform time series analysis. Time series analysis is an essential component of Data Science ...

Abstract: Several interesting problems in multirobot systems can be cast in the framework of distributed optimization. Examples include multirobot task allocation, vehicle routing, target protection, ...