pythonfix
autogluon.core 1.5.0
Fast and Accurate ML in 3 Lines of Code
Fast and Accurate ML in 3 Lines of Code
Stars: 9969, Watchers: 9969, Forks: 1118, Open Issues: 386The autogluon/autogluon repo was created 6 years ago and the last code push was 2 hours ago.
The project is extremely popular with a mindblowing 9969 github stars!
How to Install autogluon-core
You can install autogluon-core using pip
pip install autogluon-core
or add it to a project with poetry
poetry add autogluon-core
Package Details
- Author
- AutoGluon Community
- License
- Apache-2.0
- Homepage
- https://github.com/autogluon/autogluon
- PyPi:
- https://pypi.org/project/autogluon.core/
- Documentation:
- https://auto.gluon.ai
- GitHub Repo:
- https://github.com/awslabs/autogluon
Classifiers
- Scientific/Engineering/Artificial Intelligence
- Scientific/Engineering/Image Recognition
- Scientific/Engineering/Information Analysis
- Software Development
Related Packages
Errors
A list of common autogluon-core errors.
Code Examples
Here are some autogluon-core code examples and snippets.
GitHub Issues
The autogluon-core package has 386 open issues on GitHub
- [BUG] Cloning
_FULLmodel gives TypeError - optimize_for_deployment for TimeSeriesPredictor
- Update Docker Image to Match AutoGluon v1.5
- [BUG] [Chronos-2] Fine-tuned checkpoint missing after refit_full
- Small documentation inconsistency on "good" vs "medium" presets inference speed.
- [BUG] DyStack fails to complete despite having converged?
- [timeseries] Fix environment-dependent errors in PredictionCache
- Support for WarpGBM
- [Tabular] Parallel Predict Prototype
- [BUG] [tabular] Dynamic stacking and using groups is incompatible
- Support Non-CUDA Devices (e.g., MPS, XPU) for Chronos Models by Allowing Device Overrides
- Fix focal loss alpha parsing for numpy float types
- [BUG] (Including PreQuantile) TabularEnsemble in timeseries prediction cannot handle known covariates during training
- [BUG] Training fails due to fastai ImportError when already installed
- [docs] Documentation should be updated with new models
Related Packages & Articles
thinc 9.1.1
A refreshing functional take on deep learning, compatible with your favorite libraries
nlp 0.4.0
HuggingFace/NLP is an open library of NLP datasets.
allennlp 2.10.1
An open-source NLP research library, built on PyTorch.
albumentations 2.0.8
Fast, flexible, and advanced augmentation library for deep learning, computer vision, and medical imaging. Albumentations offers a wide range of transformations for both 2D (images, masks, bboxes, keypoints) and 3D (volumes, volumetric masks, keypoints) data, with optimized performance and seamless integration into ML workflows.
pytorch-nlp 0.5.0
Text utilities and datasets for PyTorch
transformers 5.2.0
Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
spacy 3.8.11
Industrial-strength Natural Language Processing (NLP) in Python
keras 3.13.2
Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. The core data structures of Keras are layers and models. The philosophy is to keep simple things simple, while allowing the user to be fully in control when they need to (the ultimate control being the easy extensibility of the source code via subclassing).
scikit-learn 1.8.0
A set of python modules for machine learning and data mining