The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
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tsfresh reviews and mentions
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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
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A note from our sponsor - WorkOS
workos.com | 26 Apr 2024
Stats
blue-yonder/tsfresh is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of tsfresh is Jupyter Notebook.
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