The terms data analysis and data visualization have become synonymous in everyday language in the wider data community, but the two are quite different. Data analysis is an exploratory process ...

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

A quantum approach to data analysis that relies on the study of shapes will likely remain an example of a quantum advantage — albeit for increasingly unlikely scenarios.

Hybrid quantum-classical algorithm accelerates dynamic mode decomposition for high-dimensional time series analysis Peer-Reviewed Publication Intelligent Computing ...

The Data Science Lab Principal Component Analysis (PCA) from Scratch Using the Classical Technique with C# Transforming a dataset into one with fewer columns is more complicated than it might seem, ...