We will use a synthetic, small-scale dataset to develop an end-to-end ML-based pipeline for RL. The project will be developed collaboratively between all participants, including facilitators. In the first round of discussions, participants will be asked a series of questions regarding the project planning, including the choice of algorithms for each of the key steps. An end-to-end notebook for record linkage will be developed collaboratively. At the end of the hands-on session, participants will present to their supervisors (e.g. ESTHER partners).
Participants will experiment with ML tools in Python, including basic data analysis and plotting packages. In addition, they will develop a customized RL pipeline.
Pre-recorded video (30min): https://youtu.be/-iiNJePTTjA
See Moodle for more!