Enhanced Book figures from "Statistics, Data Mining, and Machine Learning in Astronomy"
We're hacking figures from the textbook "Statistics, Data Mining, and Machine Learning in Astronomy"
Figure 8.10 was hacked by Beth Reid (BIDS/Berkeley Astro) and Phil Marshall (SLAC). They used MPLD3 to visualize the family of Gaussian Process curves satisfying the constraints of the data points.
Figure 9.14 was hacked by Wilma Trick and Michael Walther (both MPIA), which exploits the "interact" feature in IPython notebook to animate Random Forests. To see the interactive features, fork the repo and fire up an IPython notebook.
Submit your own hacks of the book figures by Pull Requests to this repo!