PCA is an important tool for dimensionality reduction in data science and to compute grasp poses for robotic manipulation from point cloud data. PCA can also directly used within a larger machine ...

Sparse Principal Component Analysis (sparse PCA) represents a significant advance in the field of dimensionality reduction for high-dimensional data. Unlike conventional Principal Component Analysis ...

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.

Principal Component Analysis from Scratch Using Singular Value Decomposition with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique ...

Egyptian researchers mapped soil health using data analysis & mapping tools. They found most areas had good quality, but some ...

A research team has conducted an extensive study to explore the key factors affecting coffee production in the Gedeo Zone of ...

Develop interdisciplinary skills in data science and gain knowledge of statistical analysis, data mining, and machine learning from one of the nation’s top-ranked Tier 1 research institutions. Earn ...

Purdue University’s online Master’s in Data Science will mold the next generation of data science experts and data engineers to help meet unprecedented industry demand for skilled employees. The ...

Discover what data science is, its benefits, techniques, and real-world use cases in this comprehensive guide. Data science merges statistics, science, computing, machine learning, and other domain ...