Triple Threat

The two creators of Dask sat down with David and I to talk shop around what exactly Dask is and when to use it. I also convinced Matt to be the guest on our meetup this week! so we effectively have a double dask week! Check out the video / podcast here of our first chat and be prepared for a lot more of those insights in round 2! Here is a quick overview of what we will talk about on Wednesday:

Python makes data science and machine learning accessible to millions of people around the world. However, historically Python hasn't handled parallel computing well, which leads to issues as researchers try to tackle problems on increasingly large datasets. Dask is an open source Python library that enables the existing Python data science stack (Numpy, Pandas, Scikit-Learn, Jupyter, ...) with parallel and distributed computing. Today Dask has been broadly adopted by most major Python libraries, and is maintained by a robust open source community across the world.

This talk will discuss parallel computing generally, Dask's approach to parallelizing an existing ecosystem of software, and some of the challenges we've seen in deploying distributed systems.

Finally, we'll also address the challenges of robustly deploying distributed systems, which ends up being one of the main accessibility challenges for users today. We hope that by the end of the meetup attendees will better understand parallel computing, have built intuition around how Dask works, and have the opportunity to play with their own Dask cluster on the cloud.