azureml-train-automl-client
Used for automatically finding the best machine learning model and its parameters.
Decision gist · record as of 2026-08-14
Yes, if you are already using Azure ML and want to automate model selection and tuning within that ecosystem. The package is production-stable, actively maintained, and has low install friction. No, if you need a standalone AutoML solution that does not require Azure services or if your project uses a different cloud provider or on-premises infrastructure.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Azure ML workspace setup and authentication credentials to submit AutoML jobs.
- Low install friction with a pure Python wheel.
- Active maintenance status as of 170 days since last release.
License · maintenance · safety
(unclear) — Licensed under a proprietary Microsoft license (https://aka.ms/azureml-sdk-license). License terms are not SPDX-identified, so review the linked license before use in proprietary or open-source projects.
last release 2026-02-25 (170 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 189,430 downloads/mo, #9,929 on PyPI
Alternatives
Verify before relying
pip install azureml-train-automl-client
from azureml.train.automl import AutoMLConfig- Whether Azure ML workspace and authentication setup is required before this package can be used.
- What compute or resource constraints apply when running AutoML jobs through this client.
- Whether the package includes local model training or only submits jobs to Azure services.
What it is and what it does
azureml-train-automl-client is a Python client for Azure Machine Learning's automated machine learning service. It provides the interface to submit training and test data and automatically explore model types, algorithms, and hyperparameters to find the best-performing model for your problem. The package integrates with azureml-automl-core, azureml-core, azureml-dataset-runtime, azureml-telemetry, and azureml-train-core.
Typically used within Azure ML workflows, this client abstracts away the complexity of manual model selection and tuning. It supports Python 3.8, 3.9, 3.10, and 3.11 on macOS, Windows, and Linux. The package is production-stable and actively maintained, making it suitable for teams already invested in the Azure ML ecosystem who want to reduce the time spent on model experimentation.
Use it for
- Submit a classification or regression dataset to Azure AutoML and retrieve the best model without manually trying multiple algorithms.
- Automate hyperparameter tuning for a specific model type when you have a large search space.
- Integrate automated model selection into an Azure ML pipeline or batch training job.
- Benchmark multiple model families on your dataset to identify which algorithm class performs best.
- Reduce data science iteration time by letting AutoML explore model combinations in parallel.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using Azure ML and want to automate model selection and tuning within that ecosystem.
The package is production-stable, actively maintained, and has low install friction. No, if you need a standalone AutoML solution that does not require Azure services or if your project uses a different cloud provider or on-premises infrastructure.
Install
azureml-train-automl-client on PyPI
Before you install
Low install friction with a pure Python wheel. Active maintenance status as of 170 days since last release. Depends on azureml-automl-core, azureml-core, azureml-dataset-runtime, azureml-telemetry, and azureml-train-core.
Requires Azure ML workspace setup and authentication credentials to submit AutoML jobs.
License in practice
Licensed under a proprietary Microsoft license (https://aka.ms/azureml-sdk-license). License terms are not SPDX-identified, so review the linked license before use in proprietary or open-source projects.
Quickstart
pip install azureml-train-automl-client
from azureml.train.automl import AutoMLConfigVerify before relying
- Whether Azure ML workspace and authentication setup is required before this package can be used.
- What compute or resource constraints apply when running AutoML jobs through this client.
- Whether the package includes local model training or only submits jobs to Azure services.
Package facts
| License | Not declared unclear |
| Python support | Capped below the current Python release <3.12,>=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesazureml-automl-coreazureml-coreazureml-dataset-runtimeazureml-telemetryazureml-train-core |
| Maintenance | Actively maintained 170 days since the last release |
| First released | |
| Downloads | 189,430 / month, #9,929 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: Other/Proprietary LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: azureml_train_automl_client-1.62.0-py3-none-any.whl
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See also azure-ai-ml · azureml-train-automl · databricks-automl-runtime · azureml-automl-core · azureml-train-restclients-hyperdrive · azureml-pipeline-steps · cloudml-hypertune · azureml-train-core · FLAML · azureml-train