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 ...

Abstract: DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised clustering algorithm designed to identify clusters of various shapes and sizes in noisy datasets by ...

Under the terms of the Death in Custody Reporting Act, the Justice Department is required to collect information about everyone who dies in prisons and jails across the United States. The intention ...

Gordon Scott has been an active investor and technical analyst or 20+ years. He is a Chartered Market Technician (CMT). Vikki Velasquez is a researcher and writer who has managed, coordinated, and ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

This is a simplified C++ interface to the fast implementations of hierarchical clustering by Daniel Müllner. The original library with interfaces to R and Python can be found on danifold.net and is ...

In this tutorial, we’ll build on the foundation laid in the “Arduino-Based Solar Power System Using Python & Machine Learning, Part 1” project by exploring how to intelligently select and use machine ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

If you want to learn the math behind data science and machine learning, 3Blue1Brown is the channel for you. Created by Grant Sanderson, 3Blue1Brown uses animation to explain complex mathematical ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...