Self Driven Data Science – Issue #7
Here’s this weeks lineup of data-driven articles, stories, and resources delivered faithfully to your inbox for you to consume. Enjoy and don’t forget to subscribe!
Describes how the data science team at Airbnb uses tools together to expedite the modeling process and lower the overall development costs for a specific use case of LTV modeling — predicting the value of homes on Airbnb.
Great tutorial showing how you can follow an extremely typical NLP pipeline, using popular data and popular techniques, and end up with a racist classifier that should never be deployed.
Citing stories from Nokia to Netflix, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on “thick data” — precious, unquantifiable insights from actual people — to make the right business decisions.
Love the story outlined in the first half of this article. The rest looks to expand our attention to the systems that these mechanisms support; systems in which our participation is often both transparent and involuntary.
If you want to solve some real-world problems and design a cool product or algorithm, then having machine learning skills is not enough. You need a good working knowledge of data structures. Check it out.
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Thanks for reading and have a great day!