“It doesn’t stop being magic just because you know how it works.” Terry Pratchett, The Discworld Series Welcome to the third, and final, installment of Data Science in the Wild. In Part 1 we were lost in the woods thinking about how to start a data science project. In Part
Tag: data science in the wild
In my last blog post, I talked about the importance of establishing the right team for data science projects. Here, I’m going to talk about some of the barriers that can prevent successful adoption of data science. You can read my whole "data science in the wild" blog series here.
You’ve finally done it. You managed to stay awake through the endless series of MOOC videos, and you’ve mastered the IRIS data set. You've learned that lm() will build you a pretty nifty model in R, and you can fit a Classifier with SciKit Learn. You know your Neural Net