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Saturday, August 01, 2015

Saturday Video Morning: Machine Learning Summer School Sydney 2015 (Slides and videos)


The program booklet can be downloaded here.
The lab instructions are available here.

Intro to Machine Learning (Webers)

Probabilistic Graphical Models (Domke)

Optimization (Schmidt)

Boosting (Nock)

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
(Lawrence)

Bayesian non-parametrics: Dirichlet Processes and
friends (Adams)


Natural Language Processing (Johnson)

Bayesian non-parametric methods for unsupervised models (Buntine)


Deep Learning (Qu)


Prediction Markets (Reid)
 
 
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