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Dl Workshop Series ⭐ 935

Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)

ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels

Minirocket ⭐ 137

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

Alphacsc ⭐ 105

Convolution dictionary learning for time-series

Implementation of Undecimated Fully Convolutional Neural Network for time series modeling

Anomaly_detection ⭐ 39

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

Implementation of the Random Dilated Shapelet Transform algorithm along with interpretability tools. ReadTheDocs documentation is not up to date with the current version for now.

Wavenet Time Series Forecasting ⭐ 5

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