Project Name	Stars	Packages Using This	Most Recent Commit	Total Releases	Latest Release	Open Issues	License	Language
Dl Workshop Series	935		4 months ago			1	apache-2.0	Jupyter Notebook
Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)
Rocket	240		2 years ago			1	gpl-3.0	Python
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
Minirocket	137		2 years ago			5	gpl-3.0	Python
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
Alphacsc	105		a year ago	9	May 12, 2022	31	bsd-3-clause	Python
Convolution dictionary learning for time-series
Ufcnn	39		8 years ago			2		Python
Implementation of Undecimated Fully Convolutional Neural Network for time series modeling
Anomaly_detection	39		5 years ago			2		Jupyter Notebook
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.
Convst	28	1	3 months ago	18	August 03, 2023		bsd-2-clause	Python
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		3 years ago					Python

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Dl Workshop Series ⭐ 935

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

most recent commit 4 months ago

Rocket ⭐ 240

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

most recent commit 2 years ago

Minirocket ⭐ 137

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

most recent commit 2 years ago

Alphacsc ⭐ 105

Convolution dictionary learning for time-series

total releases 9most recent commit a year ago

Ufcnn ⭐ 39

Implementation of Undecimated Fully Convolutional Neural Network for time series modeling

most recent commit 8 years ago

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.

most recent commit 5 years ago

Convst ⭐ 28

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.

dependent packages 1total releases 18most recent commit 3 months ago

Wavenet Time Series Forecasting ⭐ 5

most recent commit 3 years ago

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Alphacsc vs Dl Workshop Series

Alphacsc vs Rocket

Alphacsc vs Minirocket

Alphacsc vs Ufcnn

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Alphacsc vs Wavenet Time Series Forecasting

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