Coiled, a Dask company, is about one year old. We’ll have a more official celebration in mid-February (official date of incorporation), but I wanted to take this opportunity to talk a little bit about the journey over the last year, where that has placed us today, and what I think comes next.
Autoscaling can save money and improve performance by “right-sizing” your distributed compute clusters as workloads change. Dask does this by collecting a lot of data about the work you’re running, and scaling to a size that ensures all your pending work gets done quickly.
The Dask Heartbeat by Coiled is a bi-weekly publication intended to centralize and broadcast Dask news over the previous two weeks.
Map (Broadcast) Joins is a technique for improving join performance in data systems. Dask, like other systems, allows you to manually trigger a map join. But, thanks to optimizations built into Dask, you don’t have to. Dask will automatically implement this functionality for you.
As we’ll see in this post, researchers, data scientists, banking firms, and even government agencies use Dask across various domains.
Python is the language of choice for science and research today, in both industry and academia. A major reason for its popularity is the plethora of supporting tools available for various specific use cases, including NumPy, SciPy, pandas, Matplotlib, scikit-learn, Jupyter Project, and of course, Dask. The Scientific Python community consists of people around the …
Python, Data Science, and Machine Learning in 2020 Read More »
COVID-19 completely transformed the way the U.S. elected its next President in the 2020 Election. The process for predicting voter turnout had to be completely transformed as well.
The Dask community is highly distributed with different teams working independently. This is powerful but sometimes makes it hard for people within the community to see everything that is going on. The Dask Heartbeat by Coiled is a bi-weekly publication intended to centralize and broadcast Dask news over the previous two weeks.
Dask is a free and open-source library for parallel computing in Python. Dask helps you scale your data science and machine learning workflows. Dask makes it easy to work with Numpy, pandas, and Scikit-Learn, but that’s just the beginning. Dask is a framework to build distributed applications that has since been used with dozens of other systems like XGBoost, PyTorch, Prefect, Airflow, RAPIDS, and more. It’s a full distributed computing toolbox that fits comfortably in your hand.
On a live stream in October 2020, James Bourbeau, Dask maintainer and software engineer at Coiled, joined Hugo Bowne-Anderson to discuss and code about scalable data science deployments as a service and how he thinks about these things at Coiled.
Recently, Coiled’s Head of Marketing and Evangelism Hugo Bowne-Anderson and Software Engineer James Bourbeau were joined by Florian Jetter, Senior Data Scientist at Blue Yonder, for a Science Thursday on “Data Processing at Blue Yonder: One Supply Chain at a Time”. Blue Yonder provides software-as-a-service products around supply chain management.
