DiscoverTest & Code : Python Testing for Software Engineering126: Data Science and Software Engineering Practices ( and Fizz Buzz ) - Joel Grus
126: Data Science and Software Engineering Practices ( and Fizz Buzz ) - Joel Grus

126: Data Science and Software Engineering Practices ( and Fizz Buzz ) - Joel Grus

Update: 2020-08-171
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Description

Researches and others using data science and software need to follow solid software engineering practices. This is a message that Joel Grus has been promoting for some time.



Joel joins the show this week to talk about data science, software engineering, and even Fizz Buzz.



Topics include:




  • Software Engineering practices and data science

  • Difficulties with Jupyter notebooks

  • Code reviews on experiment code

  • Unit tests on experiment code

  • Finding bugs before doing experiments

  • Tests for data pipelines

  • Tests for deep learning models

  • Showing researchers the value of tests by showing the bugs found that wouldn't have been found without them.

  • "Data Science from Scratch" book


    • Showing testing during teaching Data Science


  • "Ten Essays on Fizz Buzz" book


    • Meditations on Python, mathematics, science, engineerign and design

    • Testing Fizz Buzz

    • Different algorithms and solutions to an age old interview question.


  • If not Fizz Buzz, what makes a decent coding interview question.

  • pytest

  • hypothesis

  • Math requirements for data science

Special Guest: Joel Grus.

Sponsored By:

Support Test & Code : Python Testing for Software Engineering

Links:

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126: Data Science and Software Engineering Practices ( and Fizz Buzz ) - Joel Grus

126: Data Science and Software Engineering Practices ( and Fizz Buzz ) - Joel Grus

Brian Okken