Comparison
autokeras vs hyperband
Verdict
Pick autokeras if autoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+; pick hyperband if hyperband optimizes hyperparameters quickly with an efficient bandit-based approach, supporting several models from scikit-learn and polylearn.
Markdown twin · autokeras alternatives · hyperband alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | autokeras | hyperband |
|---|---|---|
| Maintenance | Slowing (251d since push) As of 3w · github_public_v1 | Dormant (2910d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- autokeras
- AutoML library for deep learning
- hyperband
- Tuning hyperparams fast with Hyperband
Stars
- autokeras
- 9.3k
- hyperband
- 599
Forks
- autokeras
- 1.4k
- hyperband
- 73
Open issues
- autokeras
- 161
- hyperband
- 9
Language
- autokeras
- Python
- hyperband
- Python
Adopt for
- autokeras
- AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+.
- hyperband
- Hyperband optimizes hyperparameters quickly with an efficient bandit-based approach, supporting several models from scikit-learn and polylearn.
Persona
- autokeras
- -
- hyperband
- -
Runtime
- autokeras
- -
- hyperband
- -
License
- autokeras
- Apache-2.0
- hyperband
- Other
Last pushed
- autokeras
- Nov 25, 2025
- hyperband
- Aug 15, 2018
Categories
- autokeras
- Developer Tools, Model Training
- hyperband
- Model Training
Trust and health
Maintenance
- autokeras
- Slowing (36%)
- hyperband
- Dormant (18%)
Days since push
- autokeras
- 251d
- hyperband
- 2910d
Open issues (now)
- autokeras
- 161
- hyperband
- 9
Owner type
- autokeras
- Organization
- hyperband
- User
Full report
- autokeras
- Trust report
- hyperband
- Trust report
Shared compatibility
- Python · autokeras: Python runtime · hyperband: Python runtime
Choose autokeras if…
- License: autokeras is Apache-2.0, hyperband is Other.
- Tags unique to autokeras: autodl, automl, deep-learning, keras.
- Also covers Developer Tools.
- When your project involves deep learning tasks requiring minimal manual intervention in designing models.
When NOT to use autokeras
- When working with Python versions older than 3.7 or TensorFlow versions older than 2.8.0, as AutoKeras is not compatible.
- If your project emphasizes transparent, understandable model architecture over automated generation without human oversight.
Choose hyperband if…
- License: hyperband is Other, autokeras is Apache-2.0.
- Tags unique to hyperband: classification, gradient-boosting, hyperparameter-optimization, regression.
- Use Hyperband when you need fast optimization of hyperparameters for classifiers such as gradient boosting or regressors like factorization machines from polylearn.
When NOT to use hyperband
- Avoid Hyperband if you require custom data formats that differ significantly from scikit-learn conventions, as this will necessitate extensive customization of the load_data modules.
- Do not use Hyperband when the models you need for hyperparameter tuning are not among the eight pre-supported models; additional support is required outside what comes built-in.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (keras-team/autokeras) · observed Aug 4, 2026
- GitHub forks (keras-team/autokeras) · observed Aug 4, 2026
- Last push (keras-team/autokeras) · observed Nov 25, 2025
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zygmuntz/hyperband) · observed Aug 4, 2026
- GitHub forks (zygmuntz/hyperband) · observed Aug 4, 2026
- Last push (zygmuntz/hyperband) · observed Aug 15, 2018
- License file (Other) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: autokeras 9.3k · hyperband 599 (synced Aug 4, 2026).
Common questions
- What is the difference between autokeras and hyperband?
- autokeras: AutoML library for deep learning. hyperband: Tuning hyperparams fast with Hyperband. See the comparison table for live GitHub stats and shared categories.
- When should I choose autokeras over hyperband?
- Choose autokeras over hyperband when License: autokeras is Apache-2.0, hyperband is Other; Tags unique to autokeras: autodl, automl, deep-learning, keras; Also covers Developer Tools; When your project involves deep learning tasks requiring minimal manual intervention in designing models.
- When should I choose hyperband over autokeras?
- Choose hyperband over autokeras when License: hyperband is Other, autokeras is Apache-2.0; Tags unique to hyperband: classification, gradient-boosting, hyperparameter-optimization, regression; Use Hyperband when you need fast optimization of hyperparameters for classifiers such as gradient boosting or regressors like factorization machines from polylearn.
- When should I avoid autokeras?
- When working with Python versions older than 3.7 or TensorFlow versions older than 2.8.0, as AutoKeras is not compatible. If your project emphasizes transparent, understandable model architecture over automated generation without human oversight.
- When should I avoid hyperband?
- Avoid Hyperband if you require custom data formats that differ significantly from scikit-learn conventions, as this will necessitate extensive customization of the load_data modules. Do not use Hyperband when the models you need for hyperparameter tuning are not among the eight pre-supported models; additional support is required outside what comes built-in.
- Is autokeras or hyperband more popular on GitHub?
- autokeras has more GitHub stars (9,328 vs 599). Stars measure visibility, not whether either tool fits your constraints.
- Are autokeras and hyperband open source?
- Yes - both are open-source projects on GitHub (autokeras: Apache-2.0, hyperband: Other).
- Where can I find alternatives to autokeras or hyperband?
- GraphCanon lists graph-backed alternatives at autokeras alternatives and hyperband alternatives (autokeras markdown twin, hyperband markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, autokeras or hyperband?
- autokeras: Slowing. hyperband: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for autokeras and hyperband?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: autokeras trust report; hyperband trust report.