Fast and Accurate ML in 3 Lines of Code
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Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
- data-science
- python
- machine-learning
- pycaret
AutoML library for deep learning
- automl
- neural-architecture-search
- automated-machine-learning
- python
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
Differentiable architecture search for convolutional and recurrent networks
- deep-learning
- automl
- image-classification
- language-modeling
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
a delightful machine learning tool that allows you to train, test, and use models without writing code
- machine-learning
- machinelearning
- machine-learning-algorithms
- machine-learning-library
Automatic architecture search and hyperparameter optimization for PyTorch
- automl
- deep-learning
- tabular-data
- pytorch
Ergonomic machine learning for everyone.
- machine-learning
- neural-networks
- auto-ml
AI on the way. An auto deep learning pipe dream. An RDBMS approach to deep learning. Declarative, explainable, scalable, optimizable, easy to deploy, all that good stuff.
Python AutoML for Trading Systems and Sports Betting
- machine-learning
- predictive-analytics
- classification
- regression
WARNING: Katib project is DEPRECATED, users should migrate to OptimizationJob and Kubeflow Trainer
- ai
- automl
- huggingface
- hyperparameter-tuning
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
- vizier
- hyperparameter-optimization
- tuning
- tuning-parameters
[UNMAINTAINED] Automated machine learning for analytics & production
- machine-learning
- data-science
- automated-machine-learning
- gradient-boosting
Official Implementation of 'Fast AutoAugment' in PyTorch.
- deep-learning
- convolutional-neural-networks
- pytorch
- augmentation
Automated deep learning algorithms implemented in PyTorch.
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
- bayesian-optimization
- bayesian-optimisation
- hyperparameter-optimization
- hyperparameter-tuning
An autoML framework & toolkit for machine learning on graphs.
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
- pipeline
- pipeline-framework
- machine-learning
- deep-learning
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
- python
- pytorch
- machine-learning
- deep-learning
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.