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leeoniya / uPlot

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Tests

leeoniya
leeoniya commented Dec 14, 2019

it's becoming more time-consuming and error-prone to manually re-test all the demos following internal refactorings and API adjustments.

now that the API is fleshed out a bit, it's possible to test a large amount of code (non-granularly) without having to simulate all interactions via Puppeteer or similar.

a lot of code can already be regression-tested by simply running all the demos and val

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neural_prophet

ourownstory / neural_prophet

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tslearn-team / tslearn

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timeseriesAI / tsai

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Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

python machine-learning timeseries deep-learning time-series regression cnn pytorch rocket transformer forecasting classification rnn sequential fastai time-series-analysis time-series-classification self-supervised state-of-the-art inceptiontime
  • Updated Apr 6, 2022
  • Jupyter Notebook

shubhomoydas / ad_examples

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A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

streaming timeseries time-series lstm generative-adversarial-network gan rnn autoencoder ensemble-learning trees active-learning concept-drift graph-convolutional-networks interpretability anomaly-detection adversarial-attacks explaination anogan unsuperivsed nettack
  • Updated Feb 10, 2022
  • Python

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