autodo
AutoML framework
Develops an automated machine learning framework to improve deep learning model performance on biased and noisy data
Official PyTorch code for CVPR 2021 paper "AutoDO: Robust AutoAugment for Biased Data with Label Noise via Scalable Probabilistic Implicit Differentiation"
24 stars
3 watching
2 forks
Language: Python
last commit: about 3 years ago autoaugmentautomated-machine-learningautoml
Related projects:
| Repository | Description | Stars |
|---|---|---|
 deepwisdom/autodl | Automated deep learning algorithm that performs feature engineering, model selection, and hyperparameter tuning without human intervention. | 1,140 |
 datacanvasio/hypernets | An automated machine learning framework that simplifies the development of end-to-end AutoML toolkits in specific domains. | 267 |
 sb-ai-lab/lightautoml | A framework for creating machine learning models with minimal code and customization options | 1,235 |
 skblaz/autobot | An autoML framework for evolving text representations to support explainable text classification models | 10 |
 pku-dair/mindware | An efficient AutoML system that automates the machine learning lifecycle | 53 |
 udellgroup/oboe | Automated machine learning system for selecting promising models or pipelines for new datasets | 82 |
 axelderomblay/mlbox | Automated Machine Learning library for Python | 1,500 |
 automl/robo | A Bayesian optimization framework designed to optimize complex functions with robustness and flexibility | 484 |
| datacanvasio/cooka | An automated machine learning toolkit with visualization and feature engineering capabilities | 40 |
 a-hanf/mlr3automl | Automates machine learning task selection and model training using R's mlr3 framework | 25 |
 western-oc2-lab/automl-implementation-for-static-and-dynamic-data-analytics | Automated Machine Learning implementation for static and dynamic data analytics with a focus on IoT anomaly detection | 624 |
 thumnlab/autogl | An autoML framework for machine learning on graphs, enabling researchers and developers to automate the process of building and training neural networks on graph data. | 1,094 |
 autodistill/autodistill | Automatically trains models from large foundation models to perform specific tasks with minimal human intervention. | 2,022 |
 jvalegre/robert | Automated machine learning protocols for cheminformatics using Python | 39 |
 autoviml/autoviz | Automatically generates insightful visualizations from datasets of any size with minimal code | 1,749 |