Armando has authored books such as Python Data Analysis - Second Edition and Mastering TensorFlow, Packt Publishing. He has also published research in international journals and conferences.

This article proposes a novel data-driven adaptive robust optimization (ARO) framework based on principal component analysis (PCA). By performing PCA on uncertainty data, the correlations among ...

Kernel Principal Component Analysis (KPCA) is an alternative PCA technique that is used to deal with a similar data set. For a large-sized data set, KPCA’s execution time and occupied storage space ...