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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 algori
by Aeolus98 9y ago
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 9y agocan you elaborate on the finicky part?
- glup 9y agoI'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 9y agoI 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.