Probabilistic Machine Learning and AI

How can a machine learn from experience? Probabilistic modelling provides a mathematical framework for understanding what learning is, and has therefore emerged as one of the principal approaches for designing computer algorithms that learn from data acquired through experience.  The field of machine learning underpins recent advances in artificial intelligence, and data science, and has the potential to play an important role in scientific data analysis. I will highlight some current areas of research at the frontiers of machine learning, including our project on developing an Automatic Statistician.

日期:
演讲者:
Zoubin Ghahramani
所属机构:
University of Cambridge and Uber AI Labs

系列: Cambridge Lab PhD Summer School