nni
lightwood
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| nni | lightwood | |
|---|---|---|
| 5 | 2 | |
| 13,708 | 420 | |
| 0.8% | 3.8% | |
| 6.7 | 9.2 | |
| about 1 month ago | 8 days ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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
lightwood
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[D] What would a good ML take home test look like for you?
Create a very detailed issue about this (bonus points, you can use the same thing for all candidates to have a fair evaluation). Here's an example.
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Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database
3. A decoder that is trained to generate images takes that representation and generates an image1.
Note: above is a good illustrative example, in practice, we're good with outputting dates, numerical, categories, tags and time-series (i.e. predicting 20 steps ahead). We haven't put much work into image/text/audio/video outputs
You should be able to find more details about how we do this in the docs and most of the heavy lifting happens in the lightwood repo, the code for that is fairly readable I hope: https://github.com/mindsdb/lightwood
What are some alternatives?
optuna - A hyperparameter optimization framework
MindsDB - The platform for customizing AI from enterprise data
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
nitroml - NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.
autogluon - AutoGluon: Fast and Accurate ML in 3 Lines of Code
pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy
AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/Cream]
probability - Probabilistic reasoning and statistical analysis in TensorFlow
hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python
Projects-Archive - This hacktober fest, the only stop you’ll need to make for ML, Web Dev and App Dev - see you there!
archai - Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
funsor - Functional tensors for probabilistic programming