have labels which encode information about how the array values map to locations in space, time, etc. Xarray doesn’t just keep track of labels on arrays – it uses them to provide a powerful and concise interface
trees in parallel. 1. Prepare and clean our possibly large data, probably with a lot of Pandas wrangling 2. Set up XGBoost master and workers 3. Hand data our cleaned data from a bunch of distributed Pandas dataframes to XGBoost workers across our cluster
conventions giving you a powerful, format-agnostic interface for working with your data. It excels when working with multi-dimensional Earth Science data, where tabular representations become unwieldy and inefficient.
like Harvard medical school, Chan Zuckerberg, and Novartis 2. Finance like Barclays and Capital One 3. Geophysical Sciences like NASA, LANL, and the UK Met Oﬃce 4. Beamline facilities like Brookhaven 5. Retail like Walmart, JDA, and Grubhub` (which, as you know, is everywhere) https://youtu.be/t_GRK4L-bnw
move complex workﬂows, code, and data between the cloud and their local workstation https://coiled.io/ Prefect Prefect is a new workﬂow management system, designed for modern infrastructure and powered by open-source software. https://www.prefect.io/ Saturn Cloud Saturn Cloud enables data scientists to work at scale using the tools they know best: Python, Jupyter, and Dask https://www.saturncloud.io/
one per user) • A Proxy for proxying both the connection between the user’s client and their respective scheduler, and the Dask Web UI for each cluster • A central Gateway that manages authentication and cluster startup/shutdown
built on Dask • Dask used to beat big data benchmarks • More info on CZI funded maintainer position coming soon... Learn More Jacob Tomlinson @_jacobtomlinson Dask Website dask.org Dask Twitter @dask_dev Take the Dask 2020 survey at dask.org/survey