33: Katharine Jarmul - Testing in Data Science
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November 30, 2017
A discussion with Katharine Jarmul, aka kjam, about some of the challenges of data science with respect to testing. Some of the topics we discuss: experimentation vs testing testing pipelines and pipeline changes automating data validation property based testing schema validation and detecting schema changes using unit test techniques to test data pipeline stages testing nodes and transitions in DAGs testing expected and unexpected data missing data and non-signals corrupting a dataset with noise fuzz testing for both data pipelines and web APIs datafuzz hypothesis testing internal interfaces documenting and sharing domain expertise to build good reasonableness intermediary data and stages neural networks speaking at conferences Special Guest: Katharine Jarmul.Sponsored By:Python Testing with pytest: Simple, Rapid, Effective, and Scalable The fastest way to learn pytest. From 0 to expert in under 200 pages.Patreon Supporters: Help support the show with as little as $1 per month. Funds help pay for expenses…