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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.

Investors Are Overlooking a Big Problem With New ETFs

Volatility is a fact of life in financial markets. There’s no way to avoid it. We see it all the time in the day-to-day price ...

Madison Core Bond Fund Q4 2025 Investment Strategy Letter

For the quarter, the Madison Core Bond Fund (Class I) returned 1.11%, modestly outperforming its benchmark return of 1.10% by ...

Probability Distribution Methods to Predict Stock Profits

Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...
IEEE

Remining Useful Life Prediction Using Graph Neural Networks for Rolling Bearing

Abstract: Remaining Useful Life (RUL) prediction is a necessary tool for condition monitoring and health management of rotating machinery, which is very important to ensure safe and economical ...
IEEE

GSPO-LAD: A Graph Neural Network-Based Sensor Placement and Anomaly Detection in Water Distribution Systems

Abstract: AI-based sensor placement for anomaly detection in water distribution systems (WDS) enhances system reliability and efficiency. Advanced WDS are attractive targets for malicious actors who ...
Frontiers

Resilience optimization and dynamic stability defense in active distribution networks under extreme disasters: a graph learning and cooperative control approach

1 Guangdong Power Grid Corporation Foshan Power Supply Bureau, Foshan, China 2 Electric Power Research Institute of China Southern Power Grid, Guangzhou, Guangdong, China Introduction: The escalating ...
GitHub

Graph RAG and Hybrid RAG Workshop

The dataset used in this workshop is the BlackRock founders dataset, which are three small text files containing information about the founders of the asset management firm BlackRock. The aim of the ...