Getting started with Dask Transcripts
Chapter: Conclusion
Lecture: Thanks and goodbye
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Thank you, Michal. Finally, to end on a few different notes here. First, Dask isn't one library, it's actually dozens of libraries, all work together.
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All of these libraries are maintained by hundreds of different individuals, like yourself, spread around the
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world, working at many different institutions on many different projects. Go to the github.com/dask organization.
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You'll find lots of information about the Dask developer community. You might also want to look at the Dask documentation.
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This is at docs.dask.org and there's tons of information here if you want to dive more deeply and see the capabilities that are now available to you.
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I also highly recommend looking at examples.dask.org. This website contains dozens of fully worked examples in many different domains.
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You may find something here that speaks much more to your workloads than the exercises we've just gone through. Additionally, all of these exercises,
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you can run yourself by clicking the launch binder button, to be taken into a notebook running on the cloud where you can run Dask
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yourself. Again, on some of these different and maybe more exciting or more relevant applications
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for you. Our next course is going to be about the fundamentals of Dask, we've
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touched today here just on Dask to scale out Pandas workloads with Dask DataFrame, in
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a very simple way, but there's a lot more to Dask. As we've mentioned before,
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at the beginning of the series, Dask is used inside of many different libraries. Some of them are built into Dask, things like Dask DataFrame,
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which we've just seen. Dask Array for parallel NumPy, Dask Delayed for parallelizing general purpose Python code.
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Dask Bag for dealing with more JSON or text data, as well as things like Dask-ML for machine learning. We'll also get into using Dask in the cloud and
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figure out how to deploy these workloads at scale. So that's it. Again, thank you all for your time,
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we look forward to seeing you in our next session. Cheers!