Platforme no-code pentru Machine Learning automatizat
For platformă AutoML no-code, the strongest matches are h2oai/h2o-3 (H2O is a distributed AutoML platform that automates model), pycaret/pycaret (PyCaret is a genuine AutoML platform that automates model) and keras-team/autokeras (AutoKeras is an AutoML library that automates neural architecture). Each is ranked by relevance to your query, popularity and recent activity.
Aceste instrumente open-source permit utilizatorilor să construiască și să implementeze modele predictive fără a scrie cod de programare.
Platforme no-code pentru Machine Learning automatizat
Găsește cele mai bune repo-uri cu AI.Vom căuta cele mai potrivite repository-uri folosind AI.
- h2oai/h2o-3
h2oai/h2o-3
7,493Vezi pe GitHubh2o-3 is a distributed machine learning platform and automated machine learning framework designed for training and deploying predictive models using distributed in-memory computing. It functions as a deep learning framework and a distributed model scoring engine, capable of operating as a Kubernetes ML cluster to process large datasets in parallel. The platform distinguishes itself through automated machine learning capabilities that automatically select the best algorithms and hyperparameters to optimize model performance. It provides specialized deep learning toolkits for tasks including i
H2O is a distributed AutoML platform that automates model training, hyperparameter tuning, and feature engineering, but its description and tags do not emphasize a visual drag-and-drop interface, so it only partially addresses the no-code requirement.
Jupyter NotebookHyperparameter Optimization - pycaret/pycaret
pycaret/pycaret
9,811Vezi pe GitHubPyCaret is a Python AutoML platform and MLOps lifecycle manager designed to automate machine learning workflows. It functions as a low-code environment that leverages a scikit-learn native engine to execute preprocessing, training, and evaluation for tabular data. The platform distinguishes itself as an LLM-powered ML copilot, using large language model agents to analyze datasets, design experiment configurations, and explain model results. It also serves as a Kubernetes ML orchestrator and model registry, enabling the versioning of trained pipelines and their promotion to production API endp
PyCaret is a genuine AutoML platform that automates model training, hyperparameter tuning, and feature engineering, but it is a code-based (low-code) library rather than a visual drag-and-drop tool, so it matches the category but lacks the no-code interface you want.
PythonAutomated Machine LearningMachine Learning Workflow LibrariesAI Agent Integrations - keras-team/autokeras
keras-team/autokeras
9,320Vezi pe GitHubAutoKeras is an automated machine learning framework and Keras AutoML library designed to discover the most effective deep learning model structures for a given dataset. It functions as a tool for deep learning architecture search, eliminating manual hyperparameter tuning by automatically searching for and optimizing neural network architectures. The framework provides capabilities for benchmarking and refining neural network designs to maximize performance. It includes a system for containerized machine learning deployment, allowing environments to be packaged into containers to ensure consi
AutoKeras is an AutoML library that automates neural architecture search and hyperparameter tuning, but it is code-based rather than offering a visual drag-and-drop interface as your intent specifies, making it a genuine AutoML platform that misses the no-code feature.
PythonNeural Architecture SearchAutomated Architecture SearchBayesian Optimization
