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aglite-test-0.5.3b20221122
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مشاهده بیشترتوضیحات
AutoML for Image, Text, and Tabular Data
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | aglite-test-0.5.3b20221122 |
| نام | aglite-test |
| نسخه کتابخانه | 0.5.3b20221122 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | AutoGluon Community |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://github.com/awslabs/autogluon |
| آدرس اینترنتی | https://pypi.org/project/aglite-test/ |
| مجوز | Apache-2.0 |
<div align="left">
<img src="https://user-images.githubusercontent.com/16392542/77208906-224aa500-6aba-11ea-96bd-e81806074030.png" width="350">
</div>
## AutoML for Image, Text, Time Series, and Tabular Data
[](https://github.com/awslabs/autogluon/releases)
[](https://github.com/awslabs/autogluon/actions/workflows/continuous_integration.yml)
[](https://github.com/awslabs/autogluon/actions/workflows/platform_tests-command.yml)
[](https://pypi.org/project/autogluon/)
[](./LICENSE)
[](https://pepy.tech/project/autogluon)
[](https://twitter.com/autogluon)
[Install Instructions](https://auto.gluon.ai/stable/install.html) | Documentation ([Stable](https://auto.gluon.ai/stable/index.html) | [Latest](https://auto.gluon.ai/dev/index.html))
AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy machine learning and deep learning models on image, text, time series, and tabular data.
## Example
```python
# First install package from terminal:
# pip install -U pip
# pip install -U setuptools wheel
# pip install autogluon # autogluon==0.5.2
from autogluon.tabular import TabularDataset, TabularPredictor
train_data = TabularDataset('https://autogluon.s3.amazonaws.com/datasets/Inc/train.csv')
test_data = TabularDataset('https://autogluon.s3.amazonaws.com/datasets/Inc/test.csv')
predictor = TabularPredictor(label='class').fit(train_data, time_limit=120) # Fit models for 120s
leaderboard = predictor.leaderboard(test_data)
```
| AutoGluon Task | Quickstart | API |
|:--------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| TabularPredictor | [](https://auto.gluon.ai/stable/tutorials/tabular_prediction/tabular-quickstart.html) | [](https://auto.gluon.ai/stable/api/autogluon.predictor.html#module-0) |
| TextPredictor | [](https://auto.gluon.ai/stable/tutorials/text_prediction/beginner.html) | [](https://auto.gluon.ai/stable/api/autogluon.predictor.html#autogluon.text.TextPredictor) |
| ImagePredictor | [](https://auto.gluon.ai/stable/tutorials/image_prediction/beginner.html) | [](https://auto.gluon.ai/stable/api/autogluon.predictor.html#autogluon.vision.ImagePredictor) |
| ObjectDetector | [](https://auto.gluon.ai/stable/tutorials/object_detection/beginner.html) | [](https://auto.gluon.ai/stable/api/autogluon.predictor.html#autogluon.vision.ObjectDetector) |
| MultiModalPredictor | [](https://auto.gluon.ai/stable/tutorials/multimodal/index.html) | [](https://auto.gluon.ai/stable/api/autogluon.predictor.html#autogluon.multimodal.MultiModalPredictor) |
| TimeSeriesPredictor | [](https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-quickstart.html) | [](https://auto.gluon.ai/stable/api/autogluon.predictor.html#autogluon.timeseries.TimeSeriesPredictor) |
## Resources
See the [AutoGluon Website](https://auto.gluon.ai/stable/index.html) for [documentation](https://auto.gluon.ai/stable/api/index.html) and instructions on:
- [Installing AutoGluon](https://auto.gluon.ai/stable/index.html#installation)
- [Learning with tabular data](https://auto.gluon.ai/stable/tutorials/tabular_prediction/tabular-quickstart.html)
- [Tips to maximize accuracy](https://auto.gluon.ai/stable/tutorials/tabular_prediction/tabular-quickstart.html#maximizing-predictive-performance) (if **benchmarking**, make sure to run `fit()` with argument `presets='best_quality'`).
- [Learning with text data](https://auto.gluon.ai/stable/tutorials/text_prediction/beginner.html)
- [Learning with image data](https://auto.gluon.ai/stable/tutorials/image_prediction/beginner.html)
- [Learning with time series data](https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-quickstart.html)
Refer to the [AutoGluon Roadmap](https://github.com/awslabs/autogluon/blob/master/ROADMAP.md) for details on upcoming features and releases.
### Scientific Publications
- [AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data](https://arxiv.org/pdf/2003.06505.pdf) (*Arxiv*, 2020)
- [Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation](https://proceedings.neurips.cc/paper/2020/hash/62d75fb2e3075506e8837d8f55021ab1-Abstract.html) (*NeurIPS*, 2020)
- [Multimodal AutoML on Structured Tables with Text Fields](https://openreview.net/pdf?id=OHAIVOOl7Vl) (*ICML AutoML Workshop*, 2021)
### Articles
- [AutoGluon for tabular data: 3 lines of code to achieve top 1% in Kaggle competitions](https://aws.amazon.com/blogs/opensource/machine-learning-with-autogluon-an-open-source-automl-library/) (*AWS Open Source Blog*, Mar 2020)
- [Accurate image classification in 3 lines of code with AutoGluon](https://medium.com/@zhanghang0704/image-classification-on-kaggle-using-autogluon-fc896e74d7e8) (*Medium*, Feb 2020)
- [AutoGluon overview & example applications](https://towardsdatascience.com/autogluon-deep-learning-automl-5cdb4e2388ec?source=friends_link&sk=e3d17d06880ac714e47f07f39178fdf2) (*Towards Data Science*, Dec 2019)
### Hands-on Tutorials
- [Practical Automated Machine Learning with Tabular, Text, and Image Data (KDD 2020)](https://jwmueller.github.io/KDD20-tutorial/)
### Train/Deploy AutoGluon in the Cloud
- [AutoGluon-Tabular on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-n4zf5pmjt7ism)
- [AutoGluon-Tabular on Amazon SageMaker](https://github.com/aws/amazon-sagemaker-examples/tree/master/advanced_functionality/autogluon-tabular-containers)
- [AutoGluon Deep Learning Containers](https://github.com/aws/deep-learning-containers/blob/master/available_images.md#autogluon-training-containers)
## Contributing to AutoGluon
We are actively accepting code contributions to the AutoGluon project. If you are interested in contributing to AutoGluon, please read the [Contributing Guide](https://github.com/awslabs/autogluon/blob/master/CONTRIBUTING.md) to get started.
## Citing AutoGluon
If you use AutoGluon in a scientific publication, please cite the following paper:
Erickson, Nick, et al. ["AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data."](https://arxiv.org/abs/2003.06505) arXiv preprint arXiv:2003.06505 (2020).
BibTeX entry:
```bibtex
@article{agtabular,
title={AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data},
author={Erickson, Nick and Mueller, Jonas and Shirkov, Alexander and Zhang, Hang and Larroy, Pedro and Li, Mu and Smola, Alexander},
journal={arXiv preprint arXiv:2003.06505},
year={2020}
}
```
If you are using AutoGluon Tabular's model distillation functionality, please cite the following paper:
Fakoor, Rasool, et al. ["Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation."](https://proceedings.neurips.cc/paper/2020/hash/62d75fb2e3075506e8837d8f55021ab1-Abstract.html) Advances in Neural Information Processing Systems 33 (2020).
BibTeX entry:
```bibtex
@article{agtabulardistill,
title={Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation},
author={Fakoor, Rasool and Mueller, Jonas W and Erickson, Nick and Chaudhari, Pratik and Smola, Alexander J},
journal={Advances in Neural Information Processing Systems},
volume={33},
year={2020}
}
```
If you use AutoGluon's multimodal text+tabular functionality in a scientific publication, please cite the following paper:
Shi, Xingjian, et al. ["Multimodal AutoML on Structured Tables with Text Fields."](https://openreview.net/forum?id=OHAIVOOl7Vl) 8th ICML Workshop on Automated Machine Learning (AutoML). 2021.
BibTeX entry:
```bibtex
@inproceedings{agmultimodaltext,
title={Multimodal AutoML on Structured Tables with Text Fields},
author={Shi, Xingjian and Mueller, Jonas and Erickson, Nick and Li, Mu and Smola, Alex},
booktitle={8th ICML Workshop on Automated Machine Learning (AutoML)},
year={2021}
}
```
## AutoGluon for Hyperparameter Optimization
AutoGluon's state-of-the-art tools for hyperparameter optimization, such as ASHA, Hyperband, Bayesian Optimization and BOHB have moved to the stand-alone package [syne-tune](https://github.com/awslabs/syne-tune).
To learn more, checkout our paper ["Model-based Asynchronous Hyperparameter and Neural Architecture Search"](https://arxiv.org/abs/2003.10865) arXiv preprint arXiv:2003.10865 (2020).
```bibtex
@article{abohb,
title={Model-based Asynchronous Hyperparameter and Neural Architecture Search},
author={Klein, Aaron and Tiao, Louis and Lienart, Thibaut and Archambeau, Cedric and Seeger, Matthias},
journal={arXiv preprint arXiv:2003.10865},
year={2020}
}
```
## License
This library is licensed under the Apache 2.0 License.
نیازمندی
| مقدار | نام |
|---|---|
| ==0.5.3b20221122 | aglite-test.core |
| ==0.5.3b20221122 | aglite-test.features |
| ==0.5.3b20221122 | aglite-test.tabular |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7, <3.11 | Python |
نحوه نصب
نصب پکیج whl aglite-test-0.5.3b20221122:
pip install aglite-test-0.5.3b20221122.whl
نصب پکیج tar.gz aglite-test-0.5.3b20221122:
pip install aglite-test-0.5.3b20221122.tar.gz