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[EN] Test Driven Data Analysis - with Nick Radcliffe

Code for Thought

The History of the Python Library

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TDDA is a Python library that allows you to check data, whatever system you're using and with Jantas. It has an API that you can use from Python for all parts of it. Rec's pi is the functionality that you can give a set of examples to set a postcodes to and it will spit out ideally one or sometimes a few regular expressions that match. The third function machine, GenTest, is one where effectively you feed code and data in and it spits out tests for you.

Nick Radcliffe, data scientist and entrepreneur, talks to us about the importance of test your data. As software engineers we are familiar with test driven development. Test driven data analysis puts the same emphasis on validating and testing data for your AI app. We also dive into the Python library of the same name tdda.

Links:

https://linkedin.com/in/njradcliffe LinkedIn profile Nick Radcliffe
http://www.tdda.info Test Driven Data Analysis Blog
https://tdda.readthedocs.io/en/latest/ tdda library documentation
https://github.com/tdda/tdda TDDA GitHub repo
https://smartdatafoundry.com/ Smart Data Foundry
https://stochasticsolutions.com Stochastic Solutions - also contains links to papers and publications by Nick Radcliffe

Other libraries mentioned:

https://www.evidentlyai.com Evidently AI
https://greatexpectations.io Great Expectations

Don't forget the upcoming RSE conferences and the Hidden Ref event

https://rsecon23.society-rse.org UK RSE Conference in Swansea 5-8 September 2023
https://hidden-ref.org/festival-of-hidden-ref/ The Hidden Ref Festival, Bristol 21 September
https://un-derse23.sciencesconf.org deRSE Unconference in Jena, Germany, 26 - 28 September
https://us-rse.org/usrse23/ US RSE Conference in Chicago, USA, 16-18 October

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Thank you for listening! Merci de votre écoute! Vielen Dank für´s Zuhören!

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LinkedIn: https://www.linkedin.com/in/pweschmidt/ (personal Profile)
- LinkedIn: https://www.linkedin.com/company/codeforthought/ (Code for Thought Profile)

This podcast is licensed under the Creative Commons Licence: https://creativecommons.org/licenses/by-sa/4.0/

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