GAN-RNN_Timeseries-imputation
nl2bash
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| GAN-RNN_Timeseries-imputation | nl2bash | |
|---|---|---|
| 7 | 1 | |
| 164 | 429 | |
| - | 0.0% | |
| 0.0 | 0.0 | |
| over 1 year ago | about 2 years ago | |
| Jupyter Notebook | NewLisp | |
| MIT License | GNU General Public License v3.0 only |
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GAN-RNN_Timeseries-imputation
nl2bash
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Best Practices for Inclusive CLIs
Would there be any value in creating a document spec for CLI help output? Once there was something, individual projects could adopt it - or not, but it would be toward the goal of a future CLI ux that supports something like NL2Bash (https://github.com/TellinaTool/nl2bash) where we can create natural language interfaces to OS based services.
What are some alternatives?
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finite-element-networks - Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks" at ICLR 2022
starreduction - A free and open source tool for star removal in astronomy images. A GAN model implemented in tensorflow and trained to remove stars from astronomical images
TensorFlow2.0_Notebooks - Implementation of a series of Neural Network architectures in TensorFow 2.0
tsai - Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai