Dharhas Pothina

While most scientists aren't at the scale of black hole imaging research teams that analyze Petabytes of data every day, you can easily fall into a situation where your laptop doesn't have quite enough power to do the analytics you need. In this hands-on tutorial, you will learn the fundamentals of analyzing massive datasets with real-world examples on actual powerful machines on a public...

As we descend from the peak of the hype cycle around Large Language Models (LLMs), chat-based document inquiry systems have emerged as a high-value practical use case. Retrieval-Augmented Generation (RAG) is a technique to share relevant context and external information (retrieved from vector storage) to LLMs, thus making them more powerful and accurate.

While most scientists aren't at the scale of black hole imaging research teams that analyze Petabytes of data every day, you can easily fall into a situation where your laptop doesn't have quite enough power to do the analytics you need.

As we descend from the peak of the hype cycle around Large Language Models (LLMs), chat-based document interrogation systems have emerged as a high value practical use case.

Have you experienced the frustration of installing a new Python package, only to discover that your existing code and Jupyter notebooks no longer function as expected?

Communities are at the heart of open source software and are fundamental to our projects’ long-term success. The Python ecosystem has several mature projects, that have spent years working on community initiatives.

While most scientists aren't at the scale of black hole imaging research teams that analyze Petabytes of data every day, you can easily fall into a situation where your laptop doesn't have quite enough power to do the analytics you need. In this hands-on tutorial, you will learn the fundamentals of analyzing massive datasets with real-world examples on actual powerful machines on a public...

There are many blog posts out there that teach you how to create a map or analyze your fitbit data using Python, but what do you do when instead of a couple of thousand GPS points you have 200 billion?