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School of Electronic Engineering and Computer Science

Mr Ashish Alex


Room Number: Peter Landin, CS 440


Applied Statistics ()

The module introduces core statistical concepts for practical data analysis. It will provide students with the skills to model data sources, analyze their statistical properties, visualize them in different ways and fit the samples to a known probabilistic model.

Deep Learning for Audio and Music (Postgraduate)

This module, for those who have some prior knowledge of machine learning, focusses on deep learning methods and how they can be used to address many tasks in audio and music. The theory of modern deep neural networks (DNNs) is covered, including training of common DNN types as well as modifying DNNs for new purposes. Various tasks in analysis/generation of audio and music are studied directly to inspire the content, using raw audio and/or symbolic representations. Background in machine learning is essential, and some background in digital signal processing is highly recommended. Music knowledge would be desirable but is not a requirement.


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