ABOUT THE TALK

Recent advances in deep neural network architectures have enabled new techniques for time series classification and analysis. Using a simple data set as a running example, this talk discusses the merits of classical time series techniques, such as Wavelets, Fourier, PCA, ICA, and AR models. We then explore the merits of deep learning based time series techniques, such as CNN, RNN, and LSTM, with a particular emphasis on unsupervised methods, such as auto-encoders.

Dave Deriso

| SimpleHealth

Dave Deriso
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