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Presenter: Raul Santos Rodriguez, Turing AI Fellow and Associate Professor in Data Science and AI at the Department of Engineering Mathematics, University of Bristol
Abstract: The talk focus on how to adapt the machine learning pipeline to complex real-world situations that involve dealing with data with imperfect and weak labels. First, we describe a general approach to such problems, diving into specific applications. Then, we present an overview of techniques to derive explanations for predictions that we leverage to introduce strategies to measure and understand label quality.
This seminar is open for members of the consortium. If you want to participate as a guest please sign up.
Raul Santos Rodriguez, Turing AI Fellow and Associate Professor in Data Science and AI at the Department of Engineering Mathematics, University of Bristol
This seminar is open for members of the consortium. If you want to participate as a guest please sign up.
Raul Santos Rodriguez, Turing AI Fellow and Associate Professor in Data Science and AI at the Department of Engineering Mathematics, University of Bristol
This seminar is open for members of the consortium. If you want to participate as a guest please sign up.