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A graphic for Coiled's Science Thursday with Nicholas Sofroniew and Talley Lambert ("Interactive Image Processing at Scale").

Interactive Image Processing at Scale

Nicholas Sofroniew, Imaging Tech Lead at Chan Zuckerberg Initiative, and Talley Lambert, Microscopist and Lecturer at Harvard Medical, join Science Thursday regulars Matthew Rocklin and Hugo Bowne-Anderson to chat and code about viewing and processing large datasets, with examples from the bioimaging world. We’ll use Dask and Napari, a fast, interactive, multi-dimensional image viewer for …

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Military personnel handling unexploded ordnance.

Bomb Detection with Dask and Machine Learning

I’m trying to identify unexploded ordnance from electromagnetic data. These are basically bombs or munitions that didn’t go off and are buried in the ground somewhere. We recently spoke with Lindsey Heagy, Postdoctoral Researcher in the Department of Statistics at UC Berkeley, about her experiences with Dask. Lindsey shared how Dask significantly decreased the time …

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A graphic for Coiled's Science Thursday with Jacob Tomlinson ("Deploying and Scaling Data Science Tools on Distributed Systems").

Deploying and Scaling Data Science Tools

Jacob Tomlinson, who works at NVIDIA maintaining libraries like RAPIDS, Dask, Dask-Kubernetes and Dask-Cloudprovider, joins Matt Rocklin and Hugo Bowne-Anderson to discuss deployment and scaling of data science tools on distributed systems. Dask has many cluster manager utilities which help users set up distributed Dask clusters on a variety of different infrastructures. Dask’s distributed tooling …

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Tom Augspurger presenting at PyData NYC 2019.

Scalable Machine Learning in Python

Tom Augspurger, who works at Anaconda maintaining libraries like pandas, Dask, and Dask-ML, joins Matt Rocklin and Hugo Bowne-Anderson to discuss scalable machine learning in Python. Dask-ML provides tools for scalable machine learning. It works with libraries like scikit-learn and XGBoost to scale out to larger datasets or larger problems. We’re fortunate to have great, …

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A boat travels through the Gulf Islands near Salt Spring island, Canada. (Photographer: James MacDonald/Bloomberg)

Dask in Action with Massive Satellite Datasets

TL;DR action (noun): the most vigorous, productive, or exciting activity in a particular field, area, or group. // wants to be where the action is. We recently spoke with oceanographer, remote sensing expert, and open science advocate Chelle Gentemann, about her experiences working with massive satellite datasets and how Python and Dask make the scientific …

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Grubhub search results for "french" with "Le French Tart" as the first result.

Dask and TensorFlow in Production at Grubhub

We recently caught up with Alex Egg, Senior Data Scientists at Grubhub, about modern data science and machine learning methods to understand the intent of someone using Grubhub Search. As Alex told us, “Search is the top-of-funnel at Grubhub. That means when a user interacts with the Grubhub search engine, they want to be able …

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BlazingSQL logo

GPU-Accelerated Data Science and SQL in Python

Felipe and Rodrigo Aramburu, co-founders of BlazingSQL, join Matt Rocklin and Hugo Bowne-Anderson to discuss GPU-accelerated data science and SQL in Python. BlazingSQL is the second-largest contributor to RAPIDS, a GPU data science ecosystem, and has built a distributed SQL engine leveraging both cuDF (a pandas-like dataframe on GPUs) and Dask. GPUs are notoriously tricky, …

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Franklin Carmichael's "A Northern Silver Mine" artwork.

Interactive Computing at Scale with Dask

TL;DR Simulation isn’t reality. But with Dask, it feels like it is. In this post, we share Part 1 of our interview with Lindsey Heagy, Postdoctoral Researcher in the Department of Statistics at UC Berkeley. Lindsey shares how open-source tools like Dask helped her decrease the time it took to run her geophysical simulations by …

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Katharine Jarmul coding in a Jupyter Notebook for a Cape Python with PySpark demo on Coiled's Science Thursday.

Data Privacy and Distributed Compute

On our #ScienceThursday live stream, we recently caught up with Katharine Jarmul, Head of Product at Cape Privacy, about data privacy-enhancing techniques and when to use them; how to write policy for privacy-enhancing techniques and apply them to a pandas DataFrame; when transformations might be important during distributed data processing and how distributed computing in …

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Visualization of the GPM Core Observatory and Partner Satellites

Accelerating Science with Dask

TL;DR Many scientists can “do” science well. Few can do it well at scale. In this post, we share Part 1 of our interview with oceanographer, remote sensing expert, and open science advocate Chelle Gentemann. Chelle shares her experiences working with massive satellite datasets and how Python and Dask make the scientific process more efficient. …

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