nni
Enrichment pendingAn open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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Trust & integrity
Full report- Maintenance
- Archived (738d since push)
- As of today · Source: github_public_v1
- Provenance
- Not a fork · Organization account
- As of today · Source: github_public_v1
- Security (OSV)
- No lockfile
- As of today · Source: none
Public GitHub metadata and optional OSV dependency scans. Signals, not a guarantee. Trust methodology.
Backing
Company and funding context for Microsoft. Display-only - not part of trust score or organic ranking.
- Company
- Microsoft·GitHub org profile·today
- Employees
- 221,000·Wikidata (P1128 employees)·today
- Commercial model
- Pure OSS·GitHub org profile (public repos)·today
Overview
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 11, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 11, 2026
- Languages
- python
Source: github.language · Jul 11, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Tags
README
Installation
See the NNI installation guide to install from pip, or build from source.
To install the current release:
$ pip install nni
To update NNI to the latest version, add --upgrade flag to the above commands.
License
The entire codebase is under MIT license.