Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...

I believe there might be a minor oversight in Chapter 9.1 on PCA. It would have been helpful to mention that scaling the data is essentially required before performing PCA. Additionally, it is ...

This is Part I of a three-part series marking the 10th anniversary of the historic sentencing in the Peanut Corporation of America (PCA) criminal case. Witness to Justice Ten years ago, on Sept. 21, ...

Unlike PCA (maximum variance) or ICA (maximum independence), ForeCA finds components that are maximally forecastable. This makes it ideal for time series analysis where prediction is often the primary ...

After Pete Crow-Armstrong made two difficult, sliding catches in center field Monday, it was easy to think he's too valuable defensively to remove from the lineup. But manager Craig Counsell was ...

Getting input from users is one of the first skills every Python programmer learns. Whether you’re building a console app, validating numeric data, or collecting values in a GUI, Python’s input() ...

Functions are the building blocks of Python programming. They let you organize your code, reduce repetition, and make your programs more readable and reusable. Whether you’re writing small scripts or ...

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, ...