Novel applications of machine learning in cosmology and beyond

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With current surveys such as the Dark Energy Survey (DES), and in anticipation of even bigger projects like LSST and SKQ, the field of Astronomy is currently transitioning into an era dominated by enormous datasets. Indeed there will soon be more data than it would ever be possible to analyse, and although this influx of data could allow for a golden age of discovery, there is also the risk that the most interesting discoveries could be lost, drowned in the amount of data, never to be found. Machine learning is probably the best way we can address this problem, and in this project we aim to apply various machine learning algorithms to DES data to help analyse the data more efficiently and fuel discoveries