Rise of the machine learners: Statistical learning in the compuational era
Whether labelled as machine learning, predictive algorithms, statistical learning, or AI, the ability of computers to make real-world decisions is rising every year.
The 2019 Ihaka Lecture Series brings together four experts at the interface of statistics and computer science to discuss how computers do it, and how much we should let them.
Location | Lecture Theatre PLT1, Ground Floor, Building 303, 38 Princes Street, City Campus.
Time | 6.30pm, Wednesdays.
Refreshments will be available before each lecture at 6pm in the basement foyer, Building 303.
13 March – Open source Machine Learning @ Waikato
Professor Bernhard Pfahringer
University of Waikato
20 March – Machine Learning with TensorFlow and R
J.J. Allaire
RStudio
27 March – Algorithmic fairness: Examples from predictive models for criminal justice
Dr Kristian Lum
Human Rights Data Analysis Group (HRDAG)
3 April – Statistical learning and sparsity
Professor Robert Tibshirani
Stanford University