Open Source
Awesome AutoML Papers
A curated list of automated machine learning papers, articles, tutorials, slides and projects
Our verdict
We have not reviewed Awesome AutoML Papers 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 AutoML Papers
A community-curated GitHub repository that aggregates papers, tutorials, slides and projects on automated machine learning (AutoML). It organizes resources to help researchers and practitioners survey the field.
Best for
Researchers and machine learning engineers exploring automated machine learning literature and tools
Use cases
- Researching latest AutoML techniques and algorithms
- Finding tutorials for implementing AutoML pipelines
- Exploring open-source AutoML projects and tools
Notes
4,145 stars on GitHub. Last updated 2024-06-11. Licensed Apache-2.0.
Pros
- Curated by the community with 4,145 stars indicating trust and popularity
- Covers a broad range of resource types from papers to slides
- Free and openly accessible on GitHub
Cons
- Only a static list, no integrated tool for running AutoML
- May become outdated if not actively maintained
- Requires manual browsing to find specific resources
Key facts
What we have checked
- GitHub stars
- 4,159
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 AutoML Papers is growing
4,145 to 4,159
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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