A Python-inspired implementation of the Optimum-Path Forest classifier.
Open source
24 alternativesAwesome AutoML Papers
Curated list of automated machine learning papers, articles, tutorials, slides and projects.
About Awesome AutoML Papers
Awesome AutoML Papers is an open source GitHub repository that collects references on automated machine learning (AutoML). AutoML refers to methods that make machine learning usable by people without machine learning expertise, improve its efficiency, and speed up research in the field. The list includes papers, articles, tutorials, slides, books, and projects, grouped by subtopic.
The repository covers techniques such as automated data cleaning, automated feature engineering, hyperparameter optimization, meta-learning, and neural architecture search. It also includes a table comparing AutoML systems from several technology companies. The repository itself is a list of references and does not provide software for running AutoML.
Key features
- Survey papers on AutoML, with entries dated from 2018 to 2024
- Papers grouped by topics such as feature engineering and hyperparameter optimization
- Tutorials, articles, slides, and books grouped by topics such as Bayesian optimization
- Table comparing AutoML systems from several companies by feature engineering, hyperparameter optimization, and architecture search
- Overviews of automated data cleaning, feature engineering, and neural architecture search
- Lists of AutoML frameworks, projects, and prominent researchers
Best for: Students, researchers, and practitioners who want a organized set of references to AutoML literature and resources.
Good for
- Entries are organized by subtopic, with separate sections for papers, tutorials, articles, slides, books, and projects
- The repository is open source and includes a license file
- Readers can star the repository to follow new additions, and outside contributions are invited
Watch out for
- It is a list of links and references, not software for running AutoML
- The company comparison table shows no date or source for its entries
Awesome AutoML Papers at a glance
- Category
- AI & Machine Learning › AI for Education
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Awesome AutoML Papers FAQ
Can people contribute to the list?
Yes. The page invites readers to join as contributors.
Which AutoML topics are covered?
The page lists overviews of automated data cleaning, automated feature engineering, hyperparameter optimization, meta-learning, and neural architecture search.
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