Talks & Tutorials ================= .. raw:: html 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 `__ .. contents:: :local: 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) `__