Zac Garland, Director of Econometrics & Data Science at Mastercard Economics Institute, speaks passionately about the importance of open source and code-based approaches to data science.
A few snippets:
7:00 - The importance of open source
9:20 - The idea of "inner source" and how we use this to talk about open-source
18:08 - How to measure which model is best
32:27 - Measuring Success in data science
35:44 - Leveraging team skills regardless of technology
37:46 - Benefits of code-based data science
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What is the divide between a business analyst and a data scientist?
What is the most unique problem you've had to solve in your industry?
My leaders refer to our BI tools when asked about data science, do you consider BI data science? Why/why not?
Did you always have managing skills/people skills, or did you have to learn them?
Could you define levels of data science maturity for companies?