Renate
nni
| Renate | nni | |
|---|---|---|
| 1 | 5 | |
| 265 | 13,777 | |
| 0.8% | 0.7% | |
| 8.6 | 4.5 | |
| 4 months ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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Renate
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Renate: A Library for Real-World Continual Learning
Continual learning enables the incremental training of machine learning models on non-stationary data streams.While academic interest in the topic is high, there is little indication of the use of state-of-the-art continual learning algorithms in practical machine learning deployment. This paper presents Renate, a continual learning library designed to build real-world updating pipelines for PyTorch models. We discuss requirements for the use of continual learning algorithms in practice, from which we derive design principles for Renate. We give a high-level description of the library components and interfaces. Finally, we showcase the strengths of the library by presenting experimental results. Renate may be found at https://github.com/awslabs/renate.
nni
- Filter Pruning for PyTorch
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Automated Machine Learning (AutoML) - 9 Different Ways with Microsoft AI
For a complete tutorial, navigate to this Jupyter Notebook: https://github.com/microsoft/nni/blob/master/examples/notebooks/tabular_data_classification_in_AML.ipynb
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[D] Efficient ways of choosing number of layers/neurons in a neural network
optuna, hyperopt, nni, plenty of less-known tools too.
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Top 10 Developer Trends, Sun Oct 18 2020
microsoft / nni
What are some alternatives?
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AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/Cream]
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automlbenchmark - OpenML AutoML Benchmarking Framework
tsflex - Flexible time series feature extraction & processing
LightAutoML - LAMA - automatic model creation framework