Probabilistic Machine Learning and AI

  • Zoubin Ghahramani | University of Cambridge and Uber AI Labs

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.

系列： Cambridge Lab PhD Summer School