[Aeolus98]

A while ago I had to do a complex ML task.

It involved tons of time series data that followed a state machine, with very little training data.

A useful algorithm to force a series of noisy predictions to follow a state machine is the Viterbi decoder.

Numba let me write a JITted version that got order of magnitude improvements, especially when there were over 10^8 time series points.

It's a great piece of software, if a bit finicky sometimes.

[mtw]

can you elaborate on the finicky part?

[glup]

I've noticed two pain points: Installing outside of Anaconda can be a real chore, and error messages were extremely unhelpful (as of about 12-18 months ago, hopefully it's better now).

[dr_zoidberg]

I work on non-Anaconda environments and this single pain point has caused me to stay away from it. I do some borderline code where I need the scientific stack and Django/flask/"weby libraries", so I could never pull "going full Anaconda" on the stack.