Automating Data Science Drudgery with Pixiedust

"The Jupyter notebook has quickly become one of data scientists’ favorite tools. When using them in IBM's Watson Studio, you get a complete platform for building an application - from data preparation and analytics to building and deploying machine learning models. Jupyter notebooks are a big step up from executing code at the command line, but the basic notebook environment doesn’t do much to automate repetitive tasks. This is where Pixiedust comes in. It puts some of the most common visualization tasks behind a convenient GUI so you don’t have to remember all those obscure arguments that go into the creation of a simple bar chart. Even better, Pixiedust is extensible, so if the function you want to automate isn’t available, you can write a “PixieApp” – a Python class that extends Pixiedust – to do the job. learn how to use Pixiedust and build PixieApps."

This webcast was produced by Raj Singh, Developer Advocate at IBM

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