tsfel

Author: r0f1

README.md

@@ -700,6 +700,7 @@ https://machinelearningmastery.com/time-series-forecasting-long-short-term-memor
 ), [link](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/timeseries), [link](https://github.com/hzy46/TensorFlow-Time-Series-Examples), [Explain LSTM](https://github.com/slundberg/shap/blob/master/notebooks/deep_explainer/Keras%20LSTM%20for%20IMDB%20Sentiment%20Classification.ipynb), seq2seq: [1](https://machinelearningmastery.com/how-to-develop-lstm-models-for-multi-step-time-series-forecasting-of-household-power-consumption/), [2](https://github.com/guillaume-chevalier/seq2seq-signal-prediction), [3](https://github.com/JEddy92/TimeSeries_Seq2Seq/blob/master/notebooks/TS_Seq2Seq_Intro.ipynb), [4](https://github.com/LukeTonin/keras-seq-2-seq-signal-prediction)  
 [tspreprocess](https://github.com/MaxBenChrist/tspreprocess) - Preprocessing: Denoising, Compression, Resampling.  
 [tsfresh](https://github.com/blue-yonder/tsfresh) - Time series feature engineering.  
+[tsfel](https://github.com/fraunhoferportugal/tsfel) - Time series feature extraction.  
 [thunder](https://github.com/thunder-project/thunder) - Data structures and algorithms for loading, processing, and analyzing time series data.  
 [gatspy](https://www.astroml.org/gatspy/) - General tools for Astronomical Time Series, [talk](https://www.youtube.com/watch?v=E4NMZyfao2c).  
 [gendis](https://github.com/IBCNServices/GENDIS) - shapelets, [example](https://github.com/IBCNServices/GENDIS/blob/master/gendis/example.ipynb).