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 ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

I wasn't a big fan of Google's AI Overviews when they debuted atop Google Search. I still don't like the feature, even though it's more reliable than it was early on and, supposedly, quite popular ...

Building a chatbot can feel like an overwhelming task, especially when you’re juggling multiple tools and trying to ensure everything works seamlessly. If you’ve ever found yourself stuck between ...

Knowledge graphs have existed for a long time and have proven valuable across social media sites, cultural heritage institutions, and other enterprises. A knowledge graph is a collection of ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

Neo4j is the world's leading graph database, with native graph storage and processing.. Neo4j is the world's leading graph database, with native graph storage and processing.. Neo4j is the world's ...

The challenge of managing and recalling facts from complex, evolving conversations is a key problem for many AI-driven applications. As information grows and changes over time, maintaining accurate ...