Nba shots charts – Well, I’m in love 🙂 I like visualizations, I like sports and this post gives both the motivation and the how –
NBA players KNN – going on with the sports theme Vik Paruchuri tried to predict the points NBA player will contribute based on his nearest neighbors. I find this analysis a bit missing – first his results are not there, was this process successful or not? He looks for the most similar players to Lebron James but does not show who they are, for me that’s interesting to know, some gut feeling about the result. He uses only numeric columns which is ok, but there are also categorical variables (e.g position), why does he use them as well \ how can he use them in the future? And last but not least some visualization – for each player show me the KNN, some histogram regarding the prediction vs true values. Something.. I feel he wrote only half a post..
Rpython and pandasshell – as I see it both tools make a step toward the other. That’s an interesting questions whether they both survive. As a software developer I don’t usually see that need to switch to R.
Wining as a service – twitter vs twitter, using twitter power (+ coding + creativity 🙂 to win only twitter lotteries and competitions.
Engineers to managers – this post aroused too much thoughts to TL;DR it in only few sentences. I’m not sure it the timeline is correct or if I’ll adopt it myself but the ideas and changes about becoming a manager are inspiring and real food for thought for me.