How-To Geek on MSN

Generate realistic test data in Python fast. No dataset required

Learn the NumPy trick for generating synthetic data that actually behaves like real data.
FinanceFeeds

Crypto Machine Learning Algorithms Explained for Beginners

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Dior Could Use a Distillation

There were tailcoats made of cable knits, fit for black tie at a retirement home. Bell-curved Bar jackets and distressed ...
eWeek

Intel Teams Up With SoftBank Subsidiary on Next-Gen AI Memory

The partnership underscores intensifying global efforts to address some of AI’s biggest bottlenecks: memory performance and ...
American Library Association

American Library Association announces 2026 Youth Media Award winners

The American Library Association (ALA) today announced the top books, digital media, video and audio books for children and young adults – including the Caldecott, Coretta Scott King, Newbery and ...
Ministry of Testing

Beyond data generation: How I learned to trust synthetic data in performance testing

The first dimension is the most fundamental: statistical fidelity. It is not enough for synthetic data to look random. It must behave like real data. This means your distributions, cardinalities, and ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...