1) A short history of RAMPs: Rapid Analytics and Model Prototyping
b) design principles
c) the current tool
2) Three data challenges
a) anomaly detection in the LHC ATLAS detector
b) classifying and regressing on molecular spectra
c) time series forecasting of El Niño
3) What have we learned?
a) Course RAMPs beat single day hackatons significantly
i) larger number of students?
ii) longer RAMPs?
iii) M.Sc. students are better than data science researchers?
iv) stronger incentives?
v) closed phase preceding an open phase (vs pure open RAMP) helps to create diversity?
b) Open phase helps novice participants to catch up: the goal of teaching!
c) Sometimes also makes the best and blended score better
d) Human blending often beats machine blending
e) Human feature engineering easily beats deep learning on some data