Talks & Tutorials

Contents

Talks & Tutorials¶

Dask Tutorial¶

Dask Tutorial provides an overview of Dask and is typically delivered in 3 hours. See Parallel and Distributed Computing in Python with Dask for the latest Dask Tutorial recording from SciPy 2020.

Dask Slides¶

Dask Slides provide a quick overview of the motivation for Dask.

Dask YouTube channel¶

You can find lots of videos about Dask on the Dask YouTube channel

Presentations¶

Dask Summit 2021
- Keynotes
- Workshops and Tutorials
- Talks
PyCon US 2021
- Tutorial: Hacking Dask: Diving into Dask’s Internals (materials)
- Dask-SQL: Empowering Pythonistas for Scalable End-to-End Data Engineering
BlazingSQL Webinars, May 2021
- Intro to distributed computing on GPUs with Dask in Python (materials)
PyData DC, August 2021
- Inside Dask (materials)
PyCon US 2020
- Deploying Python at Scale with Dask
PyCon Australia 2020
- dask-image: distributed image processing for large data
PyCon Korea 2019, August 2019
- Adapting from Spark to Dask: what to expect (18 minutes)
SciPy 2019, July 2019
- Refactoring the SciPy Ecosystem for Heterogeneous Computing (29 minutes)
- Renewable Power Forecast Generation with Dask & Visualization with Bokeh (31 minutes)
- Efficient Atmospheric Analogue Selection with Xarray and Dask (18 minutes)
- Better and Faster Hyper Parameter Optimization with Dask (27 minutes)
- Dask image:A Library for Distributed Image Processing (22 minutes)
EuroPython 2019, July 2019
- Distributed Multi-GPU Computing with Dask, CuPy and RAPIDS (29 minutes)
SciPy 2018, July 2018
- Scalable Machine Learning with Dask (30 minutes)
PyCon 2018, May 2018
- Democratizing Distributed Computing with Dask and JupyterHub (32 minutes)
AMS & ESIP, January 2018
- Pangeo quick demo: Dask, XArray, Zarr on the cloud with JupyterHub (3 minutes)
- Pangeo talk: An open-source big data science platform with Dask, XArray, Zarr on the cloud with JupyterHub (43 minutes)
PYCON.DE 2017, November 2017
- Dask: Parallelism in Python (1 hour, 2 minutes)
PYCON 2017, May 2017
- Dask: A Pythonic Distributed Data Science Framework (46 minutes)
PLOTCON 2016, December 2016
- Visualizing Distributed Computations with Dask and Bokeh (33 minutes)
PyData DC, October 2016
- Using Dask for Parallel Computing in Python (44 minutes)
SciPy 2016, July 2016
- Dask Parallel and Distributed Computing (28 minutes)
PyData NYC, December 2015
- Dask Parallelizing NumPy and Pandas through Task Scheduling (33 minutes)
PyData Seattle, August 2015
- Dask: out of core arrays with task scheduling (1 hour, 50 minutes)
SciPy 2015, July 2015
- Dask Out of core NumPy:Pandas through Task Scheduling (16 minutes)

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