tsfresh
stingray
| tsfresh | stingray | |
|---|---|---|
| 4 | 1 | |
| 8,096 | 163 | |
| 0.5% | 0.6% | |
| 5.4 | 9.8 | |
| 15 days ago | 11 days ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
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tsfresh
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For deep learning practitioners in industry, is the workflow always this annoying? [D]
This is definitely a good thing to try for time-series; you can automate your feature extraction too (eg using https://github.com/blue-yonder/tsfresh ).
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[D] Incorporating external data in LSTM models for sales forecasting in e-commerce
don't forget your feature engineering -> https://github.com/blue-yonder/tsfresh
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[R] Approach to identify clusters on a time series
Rather than the exact clustering algorithm, I think the main issue here is the feature extraction for the clustering. https://github.com/blue-yonder/tsfresh might be useful for that.
- Automatic time series feature extraction based on scalable hypothesis tests
stingray
What are some alternatives?
tsflex - Flexible time series feature extraction & processing
timemachines - Predict time-series with one line of code.
TimeSynth - A Multipurpose Library for Synthetic Time Series Generation in Python
Deep_Learning_Machine_Learning_Stock - Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
PyCBC-Tutorials - Learn how to use PyCBC to analyze gravitational-wave data and do parameter inference.
SDV - Synthetic data generation for tabular data
lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Time-Series-Transformer - A data preprocessing package for time series data. Design for machine learning and deep learning.
priwo - I/O for common pulsar data formats.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
tslearn - The machine learning toolkit for time series analysis in Python