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Getting Started

  • 〰 Compute exponential moving averages with xarray and pandas accessors 〰
  • ⏱ Synchronize data streams ⏱
  • 🌡 Binning temperatures 🌡
  • 🎛 The 3-steps workflow 🎛
  • 🔭 Reconstructing the light curve of stars with LSTM 🔭
  • Sample trajectories
  • 🦎 Online linear regression with a non-stationary environment 🦎
  • 🔄 Online learning for time series prediction 🔄
  • 🔄 Online learning in non-stationary environments 🔄

Reference Documentation

  • Change log

Developer documentation

  • Installing wax
  • Running the tests
  • Type checking
  • Flake8
  • Formatting code
  • Check actions
  • Update documentation

API documentation

  • Public API: wax package
WAX-ML
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  • Welcome to WAX-ML
  • Edit on GitHub

Welcome to WAX-ML¶

WAX-ML is a library for machine-learning on streaming data.

For an introduction to WAX-ML, start at the WAX-ML GitHub page.

Getting Started

  • 〰 Compute exponential moving averages with xarray and pandas accessors 〰
  • ⏱ Synchronize data streams ⏱
  • 🌡 Binning temperatures 🌡
  • 🎛 The 3-steps workflow 🎛
  • 🔭 Reconstructing the light curve of stars with LSTM 🔭
  • Sample trajectories
  • 🦎 Online linear regression with a non-stationary environment 🦎
  • 🔄 Online learning for time series prediction 🔄
  • 🔄 Online learning in non-stationary environments 🔄

Reference Documentation

  • Change log

Developer documentation

  • Installing wax
  • Running the tests
  • Type checking
  • Flake8
  • Formatting code
  • Check actions
  • Update documentation
    • Update notebooks
    • Documentation building on readthedocs.io

API documentation

  • Public API: wax package
    • Subpackages
      • wax.modules package
      • wax.gym package
      • wax.datasets package
      • wax.universal package

Indices and tables¶

  • Index

  • Module Index

  • Search Page

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