Julia Antokhina: Testing for Data Science Hands-on Guide (ENG)

Data Fest Online 2020 ML REPA Track Testing is an underestimated and undiscovered part of Data Science development. We’ll go through motivation for testing in DS and common frameworks. While PyTest is enough for many cases, the Hypothesis for property-based testing will be mentioned as well. You will learn from examples. The main topics are: why should we write tests in Data Science, how to write tests like Pro and common applications. It encourages you to start testing as it is easy and profitable, even for DS. Посмотреть эфир и список треков и организаторов: Зарегистрироваться на фест и получить доступ к трекам: Вступить в сообщество: Соцсети Data Fest: