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In this video, Matt Rocklin gives a brief introduction to Dask Delayed in 5 minutes. Matt starts off by giving a Dask Delayed demo with simple Python code and then gets increasingly more complex as the video goes on. Dask is a free and open-source library for parallel computing in Python. Dask is a community project maintained by developers and organizations. Dask Delayed is a simple and powerful API that lets you build out custom computations with normal python code. Its often used to parallelize existing python codebases or to build out more complex algorithms. Sometimes problems don’t fit into one of the collections like dask.array or dask.dataframe. In these cases, users can parallelize custom algorithms using the simpler dask.delayed interface. The Dask delayed function decorates your functions so that they operate lazily. Rather than executing your function immediately, it will defer execution, placing the function and its arguments into a task graph. Instead of executing a function for each item in the loop in a sequential manner, Dask Delayed allows multiple items to be processed in parallel. With Dask Delayed each function call is queued, added to an execution graph, and scheduled. Share your feedback with us in the comments and let us know: Did you find the video helpful? What is your experience with using Dask Delayed? Learn more at https://docs.dask.org/en/latest/delay... KEY MOMENTS 00:00 Intro 00:29 Dask Delayed Demo 01:16 Use Dask Delayed to Parallelize 03:10 Complex Computations 04:50 Outro