Time series/ sequential data study group

Part 1 (2019)
690

Hi all,

I just wanted to let you know that during the last few weeks I’ve been updating the timeseriesAI/tsai library to make it work with fastai v2 and Pytorch 1.7. I’ve also added new functionality and tutorial nbs that may address some of the issues/ questions raised in this forum.

These are the main changes made to the library:

  • New tutorial nbs have been added to demonstrate the use of new functionality like:
    • Time series data preparation
    • Intro to time series regression
    • TS archs comparison
    • TS to image classification
    • TS classification with transformers
  • Also some tutorial nbs have been updated like Time Series transforms
  • More ts data transforms have been added, including ts to images.
  • New callbacks, like the state of the art noisy_student that will allow you to use unlabeled data.
  • New time series, state-of-the-art models are now available like:
    • XceptionTime
    • RNN_FCN (like LSTM_FCN, GRU_FCN)
    • TransformerModel
    • TST (Transformer)
    • OmniScaleCNN
    • mWDN (multi-wavelet decomposition network)
    • XResNet1d
  • Some of the models (those finishing with a Plus) have additional, experimental functionality (like coordconv, zero_norm, squeeze and excitation, etc).

The best way to discover and understand how to use this new functionality is to use the tutorial nbs. I encourage you to use them!

You can find the tsai library here: https://github.com/timeseriesAI/tsai

You’ll be able to clone the repo or pip install the library.

I hope you’ll find it useful.

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