Comparison
Hypernets vs autokeras
Verdict
Pick Hypernets if hypernets is an AutoML framework supporting multiple ML frameworks for end-to-end AutoML solutions in specific domains; 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+.
Markdown twin · Hypernets alternatives · autokeras alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | Hypernets | autokeras |
|---|---|---|
| Maintenance | Slowing (106d since push) As of 2w · github_public_v1 | Slowing (251d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | Published findings 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
- Hypernets
- A General Automated Machine Learning framework for building domain-specific AutoML toolkits.
- autokeras
- AutoML library for deep learning
Stars
- Hypernets
- 265
- autokeras
- 9.3k
Forks
- Hypernets
- 39
- autokeras
- 1.4k
Open issues
- Hypernets
- 0
- autokeras
- 161
Language
- Hypernets
- Python
- autokeras
- Python
Adopt for
- Hypernets
- Hypernets is an AutoML framework supporting multiple ML frameworks for end-to-end AutoML solutions in specific domains.
- autokeras
- AutoKeras simplifies deep learning model design through automated neural architecture search and is compatible with Python 3.7+ and TensorFlow 2.8.0+.
Persona
- Hypernets
- -
- autokeras
- -
Runtime
- Hypernets
- -
- autokeras
- -
License
- Hypernets
- Licensed under the Apache-2.0 license, allowing free use and distribution as long as copyright and licensing notices are preserved.
- autokeras
- Apache-2.0
Last pushed
- Hypernets
- Apr 20, 2026
- autokeras
- Nov 25, 2025
Categories
- Hypernets
- Developer Tools, Model Training
- autokeras
- Developer Tools, Model Training
Trust and health
Days since push
- Hypernets
- 106d
- autokeras
- 251d
Open issues (now)
- Hypernets
- 0
- autokeras
- 161
OSV dependency advisories
- Hypernets
- Published findings
- autokeras
- No lockfile (source not queried)
Full report
- Hypernets
- Trust report
- autokeras
- Trust report
Shared compatibility
- Python · Hypernets: Python runtime · autokeras: Python runtime
Choose Hypernets if…
- Tags unique to Hypernets: hyperparameter-optimization, lightgbm, pytorch, sklearn.
- If your project requires integration with TensorFlow, Keras, PyTorch, Scikit-Learn, LightGBM or XGBoost within a single AutoML pipeline
- More recently updated (last pushed Apr 20, 2026).
When NOT to use Hypernets
- If the project is limited to only traditional machine learning libraries without deep-learning needs, consider more specialized tools with narrower focus
- Avoid if your team has strict time constraints; Hypernets' setup for domain-specific AutoML might require initial investment in understanding its abstraction layer
Choose autokeras if…
- Tags unique to autokeras: autodl, deep-learning, machine-learning.
- When your project involves deep learning tasks requiring minimal manual intervention in designing models.
- More GitHub stars (9.3k vs 265) - visibility, not fit.
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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (DataCanvasIO/Hypernets) · observed Aug 4, 2026
- GitHub forks (DataCanvasIO/Hypernets) · observed Aug 4, 2026
- Last push (DataCanvasIO/Hypernets) · observed Apr 20, 2026
- 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 (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 on cards: Hypernets 265 · autokeras 9.3k (synced Aug 4, 2026).
Common questions
- What is the difference between Hypernets and autokeras?
- Hypernets: A General Automated Machine Learning framework for building domain-specific AutoML toolkits.. autokeras: AutoML library for deep learning. See the comparison table for live GitHub stats and shared categories.
- When should I choose Hypernets over autokeras?
- Choose Hypernets over autokeras when Tags unique to Hypernets: hyperparameter-optimization, lightgbm, pytorch, sklearn; If your project requires integration with TensorFlow, Keras, PyTorch, Scikit-Learn, LightGBM or XGBoost within a single AutoML pipeline; More recently updated (last pushed Apr 20, 2026).
- When should I choose autokeras over Hypernets?
- Choose autokeras over Hypernets when Tags unique to autokeras: autodl, deep-learning, machine-learning; When your project involves deep learning tasks requiring minimal manual intervention in designing models; More GitHub stars (9.3k vs 265) - visibility, not fit.
- When should I avoid Hypernets?
- If the project is limited to only traditional machine learning libraries without deep-learning needs, consider more specialized tools with narrower focus Avoid if your team has strict time constraints; Hypernets' setup for domain-specific AutoML might require initial investment in understanding its abstraction layer
- 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.
- Is Hypernets or autokeras more popular on GitHub?
- autokeras has more GitHub stars (9,328 vs 265). Stars measure visibility, not whether either tool fits your constraints.
- Are Hypernets and autokeras open source?
- Yes - both are open-source projects on GitHub (Hypernets: Apache-2.0, autokeras: Apache-2.0).
- Where can I find alternatives to Hypernets or autokeras?
- GraphCanon lists graph-backed alternatives at Hypernets alternatives and autokeras alternatives (Hypernets markdown twin, autokeras 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, Hypernets or autokeras?
- Hypernets: Slowing. autokeras: Slowing. 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 Hypernets and autokeras?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Hypernets trust report; autokeras trust report.