Exploring Time Series Using Deep Neural Networks

Student: Smirnov Denis

Educational Programme: Data Science (Master)

Final Grade: 9

Year of Graduation: 2018

Deep learning achieved state-of-the-art results in time series classification. This work summarizes achievements of deep neural networks in the problem of univariate time series classification and studies the application of recurrent neural networks to the problem. An experimental part evaluates the classification quality of different recurrent models over a collection of 85 reference datasets and compares them with existing feedforward baselines and between each other.

Full text (added May 28, 2018)

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