DIgging
Decision Intelligence for digging best parameters in target environment. (by opendilab)
auto-sklearn
Automated Machine Learning with scikit-learn (by automl)
| DIgging | auto-sklearn | |
|---|---|---|
| 1 | 3 | |
| 81 | 7,419 | |
| - | 0.6% | |
| 10.0 | 1.8 | |
| over 1 year ago | 5 months ago | |
| Python | Python | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" 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.
DIgging
Posts with mentions or reviews of DIgging.
We have used some of these posts to build our list of alternatives
and similar projects.
auto-sklearn
Posts with mentions or reviews of auto-sklearn.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-26.
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Why not AutoML every tabular data?
Efficiency Ignoring the feature engineering aspects aside, a typical data scientist workflow involves trying out the different models. Some of the AutoML modules like H2O AutoML, AutoSklearn does this for you, and allow you to interpret your models. All these save so much time experimenting with the standard models.
- [R] Regularization is all you Need: Simple Neural Nets can Excel on Tabular Data
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What free AutoML library do you recommend?
If you want a more stable AutoML library, i’ll suggest auto-sklearn which optimises performance of sklearn learning algorithms.
What are some alternatives?
When comparing DIgging and auto-sklearn you can also consider the following projects:
tiny_gp - Tiny Genetic Programming in Python
autogluon - Fast and Accurate ML in 3 Lines of Code
BayesianOptimization - A Python implementation of global optimization with gaussian processes.
Auto-PyTorch - Automatic architecture search and hyperparameter optimization for PyTorch