Hybrid Models Combine Signal Processing and Machine Learning

Day 4 of the Short Series: Signal Processing Tools for Time Series

Signal processing methods are useful because they expose structure in a time series. Fourier features reveal cycles. Wavelet features reveal changes. Online filters describe the current state of the signal.

Machine learning models are useful because they can combine many features and learn relationships that are not obvious by inspection.

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