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:

PyCharm Professional: Try PyCharm Pro for 4 months and learn how PyCharm will save you time. Promo Code: TESTANDCODE22

Links:

126: Data Science and Software Engineering Practices ( and Fizz Buzz ) - Joel Grus 32:18 Share

Test & Code

Shownotes Transcript

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