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georgeguimaraes / soothsayer

Elixir library for time series forecasting, inspired by Facebook's Prophet and NeuralProphet

Why this job: works in the areas we cover, but does not say which job it does

The soothsayer network: inputs on the left feed one dense layer per component, their sum is sliced into lag and target positions, the lag positions are subtracted from the lags before the AR branch, everything is summed into yhat, and quantile heads add offsets to a frozen copy of yhat. The predicted DataFrame lists yhat, the quantile columns and every component.

What it does

Soothsayer is an Elixir library for time series forecasting, inspired by Facebook's Prophet and NeuralProphet. It decomposes your time series into interpretable components (trend, seasonality, auto-regression, events, regressors) and uses neural networks to learn the patterns. On plain series it lands where Prophet does, and when a series has more to it there are the neural pieces: auto-regression, lagged regressors, networks on regressors, and one model over many series.

Get started

No single install command. Read the steps in the README (opens in new tab)

Maintenance
Active
Last commit 17 days ago
Stars
142
On GitHub
Licence
Apache-2.0
Allows business use
Downloads for
None listed
No release files
Latest version
v1.3.0
Released 17 days ago
Built with
Elixir
97% of the code

Is it looked after?

Contributors
Not stated
Last 90 days
Issues
100% closed
0 still open
Pull requests
37 merged
2 waiting
Releases
14
12 in the last year
  • No contributing guide
  • No security policy
  • No code of conduct

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More: languages, topics and project record

Languages

  • Elixir 97%
  • HTML 3%

Topics

  • axon
  • elixir
  • forecasting
  • machine-learning
  • neural-networks
  • neuralprophet
  • nx
  • time-series

Project record

  • JobOther AI tools
  • StatusListed
  • Commits196
  • Forks2
  • Watching3
  • Stars in 28 days+1
  • CreatedJul 17, 2024
  • First seen by usNov 7, 2026
  • CheckedNov 10, 2026

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