dnn.cool
A framework for multi-task learning, where you may precondition tasks and compose them into bigger tasks. Conditional objectives and per-task evaluations and interpretations. (by hristo-vrigazov)
nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. (by microsoft)
| dnn.cool | nni | |
|---|---|---|
| 1 | 5 | |
| 49 | 13,991 | |
| - | - | |
| 4.2 | 1.8 | |
| over 3 years ago | 9 months ago | |
| Python | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
dnn.cool
Posts with mentions or reviews of dnn.cool.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Multitask Regression
Self-promotion, but I made a framework exactly for this use case :) https://github.com/hristo-vrigazov/dnn.cool
nni
Posts with mentions or reviews of nni.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-10-04.
- 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?
When comparing dnn.cool and nni you can also consider the following projects:
Super-SloMo - PyTorch implementation of Super SloMo by Jiang et al.
optuna - A hyperparameter optimization framework
flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
autogluon - Fast and Accurate ML in 3 Lines of Code
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.