Date: 10.09.2024, 15:30-17:00
Room: Auditorium
Speakers
Gaël Varoquaux, INRIA
Motivation
Tables typically require much data preparation before feeding to a machine learning model. I will explore this preprocessing and how skrub can help. In particular, I will hint at some advanced features coming up in skrub to bridge ML to database practice.
- 1. Particularities of tabular data
- 2. Missing values
- 3. Categorical and string values
- 4. Advanced pipelining
Speakers
Gaël Varoquaux
Gaël Varoquaux is a research director working on data science at Inria (French computer science national research) where he leads the Soda team. Varoquaux’s research covers fundamentals of artificial intelligence, statistical learning, natural language processing, causal inference, as well as applications to health, with a current focus on public health and epidemiology. He also creates technology: he co-funded scikit-learn, one of the reference machine-learning toolboxes, and helped build various central tools for data analysis in Python. Varoquaux has worked at UC Berkeley, McGill, and university of Florence. He did a PhD in quantum physics supervised by Alain Aspect and is a graduate from Ecole Normale Superieure, Paris.