kaggle

Competing in a machine learning competition on Kaggle is a kind of rite of passage for data scientists.  Losing unexpectedly at the very end of the contest is also something that a lot of us have experienced.  It's not just bad luck: a very specific combination of overfitting on popular competitions can take someone who is in the top few spots in the final days of a contest and bump them down hundreds of slots in the final tally.

How to Lose at Kaggle

Want to know what's going on in data science these days?  There's no better way than to analyze a survey with over 16,000 responses that recently released by Kaggle.  Kaggle asked practicing and aspiring data scientists about themselves, their tools, how they find jobs, what they find challenging about their jobs, and many other questions.  Then Kaggle released an interactive summary of the data, as well as the anonymized dataset itself, to help data scientists understand the trends in the data.  In this episode, we'll go through some of the survey toplines that we found most interesting and counterintuitive.

kaggle

Yasaman Haghpanah