Source: Axel de Romblay, 2019 MLBox 0.8.2
Awesome AutoML
Awesome AutoML is a curated list of automated machine learning libraries and tools, inspired by awesome-automl-papers, awesome-AutoML-and-Lightweight-Models, awesome-AutoML, awesome-automl and other repositories.
Comparison
Labels
| Supported | Not supported | Unknown | |
|---|---|---|---|
| Label |
Table
| Name | Source | Classification | Regression | Clustering | Time series | Image Classification | Object Detection | NLP Tasks | Data cleaning | Feature Engineering | Feature Selection | Hyperparameter Tuning | Model Selection | Model Evaluation |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AutoGluon | https://github.com/awslabs/autogluon | |||||||||||||
| AutoKeras | https://github.com/keras-team/autokeras | |||||||||||||
| Auto-PyTorch | https://github.com/automl/Auto-PyTorch | |||||||||||||
| auto-sklearn | https://github.com/automl/auto-sklearn | |||||||||||||
| FEDOT | https://github.com/nccr-itmo/FEDOT | |||||||||||||
| LightAutoML | https://github.com/sberbank-ai-lab/LightAutoML | |||||||||||||
| NNI | https://github.com/microsoft/nni | |||||||||||||
| TPOT | https://github.com/EpistasisLab/tpot |
Latest update
Updated on 24. June 2023 07:22:10 UTC