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 ...

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.

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 ...

Harvard University presents its eight-week online course through edX, which imparts to students essential knowledge of ...

Microsoft Excel’s Data Analysis Toolpak is an invaluable add-in for those who require complex statistical or engineering analyses. This powerful feature allows ...

If you have lots of spreadsheets you would like to analyze, but unfortunately don’t have the time to invest in trawling through each one to any great depth, but known they contain a wealth of valuable ...

Q. You explained Excel’s Scenario Manager in your November 2024 Tech Q&A article and Goal Seek in your December 2024 Tech Q&A article. Can you please explain the final What-If Analysis tool: Data ...

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 ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. (Related posts: 5 things to keep in mind when you hear about Gen Z, Millennials, ...