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 ...

Simplify complex datasets using Principal Component Analysis (PCA) in Python. Great for dimensionality reduction and visualization. A ‘Trump class’ folly on the high seas Democratic voter turnout ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

47% of companies cite enhanced information exchange for investing in 2D barcodes "In today's fast-paced, data-driven supply chain environment, outdated logistics systems, fragmented labeling practices ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Personally identifiable information has been found in DataComp CommonPool, one of the largest open-source data sets used to train image generation models. Millions of images of passports, credit cards ...

While many Nintendo Switch 2 games offer upgrades from their Switch 1 counterparts, Square Enix's upcoming Dragon Quest 1 & 2 HD-2D Remake won't be one of them. In a lengthy Q&A, the publisher has now ...

Being able to quantify a surface finish is both a complex and necessary task. While surface topography relates to a three-dimensional property, the most accepted surface measurement parameter is ...

1 Faculty of Medicine, Department of Anatomy, Cell Biology and Physiological Sciences, American University of Beirut, Beirut, Lebanon 2 International Ph.D. Program in Medicine, College of Medicine, ...

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