Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

Automatic Data Processing, Inc. remains a Sell as valuation at 22x earnings is expensive relative to mid single-digit growth and macro headwinds. Recent results from ADP showed 6% revenue growth and ...

This repository contains the implementation of topological data analysis (TDA) methods for detecting adversarial examples in deep learning models, particularly focusing on Vision-Language models like ...

We often hear that “Who remembers the one who comes second?” The term ‘secondary’ is often associated with something less important, isn’t it? But today I tell you the importance of secondary in today ...

Here we present example workflows to perform a large scale untargeted metabolomics LC-MS/MS data preprocessing for molecular networking analysis using GNPS. The data set is described in Nothias, L.F.

Five pitfalls to avoid by Michael Luca and Amy C. Edmondson Let’s say you’re leading a meeting about the hourly pay of your company’s warehouse employees. For several years it has automatically been ...

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 ...

Wrapping up a multi-week series on Crafting Data Personas. What are they, why are they important, and how to get started. Continuing from last week, we’re diving right into examples of personas. I ...

ABSTRACT: Mental disorders, including depression, bipolar disorder, and mood disorders, affect millions of individuals worldwide, significantly impacting their quality of life. Early and accurate ...