Under appreciated by people just now getting into time series regression, who may be really excited about throwing deep learning at the problem.

Edit: literally saw this happen two weeks ago by a PhD in electrical engineering.

So much that! Also under appreciated: plots and OLS.

Start plotting before firing up the GPUs, then compare to standard OLS - like in this article!

Suggested reading if you don't know OLS: ML from scratch.

Well to be fair if you use a convolutional recurrent architecture, you're doing it without realizing it.

Is that true? I would think that would be more like a wavelet transform where the wavelets are learned?

Yeah, that's true.

and not a single DS/ML person seems to have ever heard of it.

Because most folks in DS/ML are working on predicting likelihood to press a button. You don’t need Fourier transforms for that.

CNN is essentially a FT with learnable kernels.

well, it’s certainly usually convolution. Hardly anyone knows why or how that connects to the FT though.

you do, depending on your feature preprocessing.

Most DS/ML people are useless chimps.

FWIIW I've used it all the time, along with wavelets, cepstrums, lifters and Hilbert transforms. For timeseries with nonlinearities and lots of data points, it's the way to go. 9/10 times I'd rather hire a EE with signal processing background than a statistician or data scientist for time series work.