Discover Data Science Testing with Laveena Ramchandani

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Up first on Friday, it’s @laveenaramchandani01 talking all things data science. I come from a data science background so I’m excited to see how this ties into testing :eyes:

Are you currently involved with any data work?

Get your questions asked here during the talk and we’ll do our best to get them all answered live. Remember that liking any questions already asked will increase the chances of them being answered live in the talk.

We’ll also use this thread to share resources then after the talk so don’t worry if you missed any :slight_smile:

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how open did you find the data scientists regarding working with a tester, were they open to the idea

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How do you deal with bias’ in test data when dealing with models

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Thanks, Laveena! What are some of the key differences between data science and AI - both in terms of the system under test, and how to approach / considerations for testing?

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How can you verify that the prediction of the model is correct, when what’s involved in making a prediction can be quite complicated and every human making a manual prediction could come up with a different result? Is there a difference between testing the model and the implementation of the model?

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What did you mean by make sure that bugs aren’t repeatable? Surely you need to be able to reproduce a bug so that the developers of the system can recreate the behaviour so they can fix it.

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What’s an interesting bug you have found?

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How do you records your Test results for Data Science?

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