In the Spring of 2023 before starting my PhD, I worked a couple of months as a freelancer. Among the different data science projects, I collaborated with a biotech company in Paris whose name cannot be disclosed for confidentiality reasons. They develop a clinical test whose purpose is to be
Main Contributions * Theoretical generalization of Q-learning to multi-objective environments * Implementation of a proof-of-concept on synthetic examples * Dashboard visualization of performance over time Preview Abstract Hyperparameter tuning of complex systems is a problem that relies on many decision-making algorithms and hand-crafted heuristics. Developers are often called upon to tune these hyperparameters
I have created a Python template that makes running ML experiments on AWS convenient so you too can take advantage of massive cloud compute for your projects. This cuts down the experiment cycle time, allows you to batch multiple experiments together, and boosts overall productivity. Motivation Waiting for scripts to
How to scale up Machine Learning using AWS, Docker, WandB, and Python.