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: TESTANDCODE20
Support Test & Code : Python Testing for Software Engineering
Links:
<p>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.</p> <p>Joel joins the show this week to talk about data science, software engineering, and even Fizz Buzz.</p> <p>Topics include:</p> <ul> <li>Software Engineering practices and data science</li> <li>Difficulties with Jupyter notebooks</li> <li>Code reviews on experiment code</li> <li>Unit tests on experiment code</li> <li>Finding bugs before doing experiments</li> <li>Tests for data pipelines</li> <li>Tests for deep learning models </li> <li>Showing researchers the value of tests by showing the bugs found that wouldn't have been found without them.</li> <li>"Data Science from Scratch" book <ul> <li>Showing testing during teaching Data Science</li> </ul></li> <li>"Ten Essays on Fizz Buzz" book <ul> <li>Meditations on Python, mathematics, science, engineerign and design</li> <li>Testing Fizz Buzz</li> <li>Different algorithms and solutions to an age old interview question.</li> </ul></li> <li>If not Fizz Buzz, what makes a decent coding interview question.</li> <li>pytest</li> <li>hypothesis</li> <li>Math requirements for data science</li> </ul><p>Special Guest: Joel Grus.</p><p>Sponsored By:</p><ul><li><a href="https://ift.tt/2JDHRTz" rel="nofollow">PyCharm Professional</a>: <a href="https://ift.tt/2JDHRTz" rel="nofollow">Try PyCharm Pro for 4 months and learn how PyCharm will save you time.</a> Promo Code: TESTANDCODE20</li></ul><p><a href="https://ift.tt/2tzXV5e" rel="payment">Support Test & Code : Python Testing for Software Engineering</a></p><p>Links:</p><ul><li><a href="https://ift.tt/2DPr3MD" title="Ten Essays on Fizz Buzz (with discount) by Joel Grus" rel="nofollow">Ten Essays on Fizz Buzz (with discount) by Joel Grus</a></li><li><a href="https://www.youtube.com/watch?v=7jiPeIFXb6U" title="I don't like notebooks. (presentation)" rel="nofollow">I don't like notebooks. (presentation)</a></li></ul>from Planet Python
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