Awesome LLMOps
Section: AutoML · an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
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Appears in 4 awesome lists
an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
Section: AutoML · an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
Section: AutoML · Automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
Section: AutoML · Framework to automate algorithm and hyperparameter tuning for sklearn.
Section: Automated Machine Learning · An AutoML toolkit and a drop-in replacement for a scikit-learn estimator.
MindsDB is an Explainable AutoML framework for developers. With MindsDB you can build, train and use state of the art ML models in as simple as one line of code.
Optuna is an automatic hyperparameter optimization software framework, particularly designed for machine learning.
Python library with multiple transformers to engineer and select features for machine learning models. scikit-learn compatible with fit() and transform() methods for encoding, imputation, variable transformation, and feature selection. BSD-3-Clause licensed.
Python library for automatic extraction of relevant features from time series.
Tool that automatically creates and optimizes machine learning pipelines using genetic programming. Consider it your personal data science assistant, automating a tedious part of machine learning.
Open-source Python library for automated feature engineering. Transforms transactional and relational datasets into feature matrices for machine learning using Deep Feature Synthesis with reusable primitives. BSD-3-Clause licensed.
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
Deep learning training platform with integrated support for distributed training, hyperparameter tuning, smart GPU scheduling, experiment tracking, and a model registry.