Sklearn-genetic-opt
nni
| Sklearn-genetic-opt | nni | |
|---|---|---|
| 6 | 5 | |
| 273 | 13,742 | |
| - | 0.5% | |
| 4.6 | 6.7 | |
| about 23 hours ago | about 2 months ago | |
| Python | Python | |
| MIT License | MIT License |
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Sklearn-genetic-opt
- GitHub - rodrigo-arenas/Sklearn-genetic-opt: Hyperparameters tuning and feature selection, using evolutionary algorithms.
- New Python AutoML Package
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Looking for contributors AutoML project in Python
The project is open for collaborators of different levels of expertise, there are some issues about new features, enchacements on docs, etc. Repo: https://github.com/rodrigo-arenas/Sklearn-genetic-opt
- I've been working on an machine learning hyperparameters tuning open source project
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Looking for open source contributors: AutoML
Here is the repo: https://github.com/rodrigo-arenas/Sklearn-genetic-opt
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Introducing Sklearn-genetic-opt: Hyperparameters tuning using evolutionary algorithms [project]
If you want to know more the details or contribute, you can check the Github repository
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?
genetic-algorithm-in-python - A genetic algorithm written in Python for educational purposes.
optuna - A hyperparameter optimization framework
evalml - EvalML is an AutoML library written in python.
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
sklearn-deap - Use evolutionary algorithms instead of gridsearch in scikit-learn
autogluon - Fast and Accurate ML in 3 Lines of Code
de-torch - Minimal PyTorch Library for Differential Evolution
AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/Cream]
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python
FEDOT - Automated modeling and machine learning framework FEDOT
archai - Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.