From the Fastml extra twitter feed here are the slides and videos of the Machine Learning Summer School Sydney 2015
The program booklet can be downloaded here.
The lab instructions are available here.
Intro to Machine Learning (Webers)
Probabilistic Graphical Models (Domke)
Computational Information Geometry and Machine Learning (Nielsen)
ML for Recommender Systems (Karatzoglou)
Structured Prediction for Computer Vision (Gould)
Bayesian inference and MCMC (Carpenter)
Approximate Inference (Ihler)
Stan Hands-on (Carpenter)
Bayesian non-parametrics: Gaussian Processes
Bayesian non-parametrics: Dirichlet Processes and
Natural Language Processing (Johnson)
Bayesian non-parametric methods for unsupervised models (Buntine)
Deep Learning (Qu)
Prediction Markets (Reid)
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