Evidence tier Source Confirmed · 9 captures on record
What the publisher says
As described on Microsoft Marketplace.
AutoGluon is an open-source AutoML (Automated Machine Learning) framework designed to help developers, data scientists, and machine learning engineers build highly accurate machine learning models with minimal coding. It automates key machine learning tasks such as data preprocessing, model selection, hyperparameter optimization, model training, and ensemble creation.
The solution supports a wide range of machine learning workflows including tabular data prediction, time series forecasting, multimodal learning, text processing, and image classification. AutoGluon is ideal for rapid model development, experimentation, predictive analytics, and production-oriented machine learning workloads.
Show the rest of the publisher’s description (14 more lines)
Features of AutoGluon:
- Automated machine learning with minimal coding requirements.
- Supports tabular data classification and regression.
- Supports time series forecasting and multimodal machine learning.
- Automatic model selection, training, and hyperparameter optimization.
- Advanced ensemble learning for improved prediction accuracy.
- Supports integration with Python-based data science and machine learning workflows.
Usage instructions for AutoGluon:
$ sudo su
$ cd /opt
$ cd autogluon
$ source venv/bin/activate
$ pip show autogluon
Disclaimer: AutoGluon 1.5.0 is provided “as is” under applicable open-source licenses. Users are responsible for proper configuration, dataset preparation, model validation, resource management, and evaluation of machine learning results. This solution is best suited for machine learning development, automated model training, predictive analytics, experimentation, and production-oriented AI workloads.
Agent build and provenance
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The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment · as of 2026-08-29
Sources
Publisher resources
1 linkLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.