and Model Prototyping.
During the RAMP, the participants submit predictive solutions (code). The models are trained on our back-end. The scores are displayed on a leaderboard. In the open phase, all participants have access to all code, and they are encouraged to look at and to reuse each other's solutions. This accelerates the development process since good ideas spread fast.
During the RAMP we blend the best models, usually achieving a better score than the best submission. Since code is submitted, the blended prototype can be delivered to the organizer, ready to be inserted into a production pipeline, either as code or by exposing it through and API.
A great tool to learn data science! Since all code is open, novice participants can learn from the pros. RAMPs are used in the MS Big Data at Telecom ParisTech, in three UPSaclay M2 programs (Data Science, AIC, Data and Knowledge), in M1 at Polytechnique, and in various in courses beyond Saclay.
RAMPs attract participants coming from different backgrounds and carreer stages who usually meet for the first time. They develop a working relationship in a relaxed environment, and sometimes keep working together after the event.
RAMPs are organized by the Paris Saclay Center for Data Science: A multi-disciplinary initiative to define, structure, and manage the data science ecosystem at the University Paris-Saclay.