Open Source · Observability
Awesome AutoDL
Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)
Our verdict
We have not reviewed Awesome AutoDL yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About Awesome AutoDL
A curated list of AutoDL resources and an in-depth analysis arguing that neural architecture search is not the end. It aggregates papers, tools, and frameworks for automated deep learning in a structured GitHub repository. The project is community-maintained and written in Python.
Best for
Researchers and practitioners exploring automated deep learning and neural architecture search
Use cases
- Surveying state-of-the-art AutoDL research and tools
- Identifying gaps and future directions in neural architecture search
- Building or comparing automated machine learning pipelines
Notes
2,337 stars on GitHub. Last updated 2022-09-26. Licensed MIT.
Pros
- Comprehensive collection of AutoDL references in one place
- Includes critical analysis beyond simple listing
- Active community with over 2,300 stars
Cons
- Not a runnable tool, only a curated list and analysis
- May become outdated without regular maintenance
- Limited to Python ecosystem and deep learning focus
Key facts
What we have checked
- GitHub stars
- 2,344
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How Awesome AutoDL is growing
2,337 to 2,344
Sources
Where this comes from
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
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