Home/Compare/hyperopt vs autokeras

Comparison

hyperopt vs autokeras

Verdict

Pick hyperopt if hyperopt offers distributed asynchronous hyperparameter optimization with multiple optimizers like TPE and Annealing; 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 · hyperopt alternatives · autokeras alternatives

GraphCanon updated 3w

hyperopt logo

hyperopt

hyperopt/hyperopt

7.6kpushed Aug 3, 2026
vs
autokeras logo

autokeras

keras-team/autokeras

9.3kpushed Nov 25, 2025

Trust & integrity

Signalhyperoptautokeras
Maintenance
Very active (0d since push)
As of 3w · github_public_v1
Slowing (251d since push)
As of 3w · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Organization 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

hyperopt
Distributed Asynchronous Hyperparameter Optimization in Python
autokeras
AutoML library for deep learning

Stars

hyperopt
7.6k
autokeras
9.3k

Forks

hyperopt
1.1k
autokeras
1.4k

Open issues

hyperopt
9
autokeras
161

Language

hyperopt
Python
autokeras
Python

Adopt for

hyperopt
Hyperopt offers distributed asynchronous hyperparameter optimization with multiple optimizers like TPE and Annealing.
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

hyperopt
-
autokeras
-

Runtime

hyperopt
-
autokeras
-

License

hyperopt
Other
autokeras
Apache-2.0

Last pushed

hyperopt
Aug 3, 2026
autokeras
Nov 25, 2025

Categories

hyperopt
Model Training
autokeras
Developer Tools, Model Training

Trust and health

Maintenance

hyperopt
Very active (96%)
autokeras
Slowing (36%)

Days since push

hyperopt
0d
autokeras
251d

Open issues (now)

hyperopt
9
autokeras
161

Full report

hyperopt
Trust report
autokeras
Trust report

Shared compatibility

  • Python · hyperopt: Python runtime · autokeras: Python runtime

Choose hyperopt if…

  • License: hyperopt is Other, autokeras is Apache-2.0.
  • Tags unique to hyperopt: annealing, asynchronous, distributed-computing, hyperparameter-optimization.
  • When you need to optimize machine learning model parameters on a distributed system asynchronously.

When NOT to use hyperopt

  • If your project does not support asynchronous execution, opting for synchronous tools might be more suitable.
  • Avoid if you prefer a simpler setup without the complexity of distributed systems and instead need straightforward hyperparameter tuning options.

Choose autokeras if…

  • License: autokeras is Apache-2.0, hyperopt 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.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: hyperopt 7.6k · autokeras 9.3k (synced Aug 4, 2026).

Common questions

What is the difference between hyperopt and autokeras?
hyperopt: Distributed Asynchronous Hyperparameter Optimization in Python. autokeras: AutoML library for deep learning. See the comparison table for live GitHub stats and shared categories.
When should I choose hyperopt over autokeras?
Choose hyperopt over autokeras when License: hyperopt is Other, autokeras is Apache-2.0; Tags unique to hyperopt: annealing, asynchronous, distributed-computing, hyperparameter-optimization; When you need to optimize machine learning model parameters on a distributed system asynchronously.
When should I choose autokeras over hyperopt?
Choose autokeras over hyperopt when License: autokeras is Apache-2.0, hyperopt 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 avoid hyperopt?
If your project does not support asynchronous execution, opting for synchronous tools might be more suitable. Avoid if you prefer a simpler setup without the complexity of distributed systems and instead need straightforward hyperparameter tuning options.
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 hyperopt or autokeras more popular on GitHub?
autokeras has more GitHub stars (9,328 vs 7,598). Stars measure visibility, not whether either tool fits your constraints.
Are hyperopt and autokeras open source?
Yes - both are open-source projects on GitHub (hyperopt: Other, autokeras: Apache-2.0).
Where can I find alternatives to hyperopt or autokeras?
GraphCanon lists graph-backed alternatives at hyperopt alternatives and autokeras alternatives (hyperopt 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, hyperopt or autokeras?
hyperopt: Very active. 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 hyperopt and autokeras?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: hyperopt trust report; autokeras trust report.

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