Anthony Blaom

Anthony Blaom is a mathematician, publishing chiefly in the areas of differential geometry and dynamical systems, and a scientific computing consultant. He is a co-creator and lead contributor for MLJ, an open-source machine learning platform written in Julia, which began as a project at the Alan Turing Institute, London.

Initially trained as an a mechanical engineer, Anthony earned a PhD in Mathematics at Caltech in 1998. He is currently a Senior Research Fellow in the Department of Computer Science, University of Auckland.


Sessions

3min
Training deep learners and other iterative models with MLJ
Anthony Blaom

MLJ.jl (Machine Learning in Julia) is a is a toolbox written in Julia providing meta-algorithms for selecting, tuning, evaluating, composing and comparing over 150 machine learning models written in Julia and other languages. We describe new developments enabling a user to wrap iterative models , such as a gradient tree booster or a Flux neural network, in a "control strategy". Wrapping hyper-parameter tuning in a control strategy is a particularly powerful possibility discussed.