Everyone seems to be talking about reproducible research, but how do you actually make sure that your work actually is fully reproducible? Rachael Tatman shows you how to take an existing research project (either your own or a provided example) and make it fully reproducible using Kaggle Kernels. You’ll learn best practices for and get hands-on experience with each of the three components necessary for completely reproducible research:
Rachael Tatman is a data scientist at Kaggle. She holds a PhD in linguistics from the University of Washington, with a focus in computational sociolinguistics. Her interests include data science education and fairness in machine learning.
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