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Scikit-Optimize on Ubuntu 26.04 with maintenance support by kCloudHubs

kCloudHubs LLC · Software Development

No attestation published

Certification per AWS Marketplace.

Provenance reach4 of 12 layers traced

Evidence tier Source Confirmed · 4 captures on record

User ratingNot rated0 reviews on the listing
Runs onUnknownVirtual machine
ProvenanceUnknown44% of the provenance layers this product can disclose
Evidence riskHighSign in to see the basis for this band.

What the publisher says

As described on AWS Marketplace.

<h3>Scikit-Optimize on Ubuntu 26.04 with Free Maintenance Support by kCloudHubs</h3>

<p>

Show the rest of the publisher’s description (32 more lines)

kCloud maintains Scikit-Optimize on Ubuntu 26.04 for machine learning optimization and hyperparameter tuning, where Bayesian optimization, model performance tuning, and efficient experimentation are critical.

</p>

<h3>Tech Use Cases</h3>

<ul>

<li>Hyperparameter optimization for machine learning models</li>

<li>Bayesian optimization for computationally expensive functions</li>

<li>Improving ML workflow efficiency and model accuracy</li>

<li>Automating parameter search in AI pipelines</li>

</ul>

<h3>Available Now on AWS Marketplace</h3>

<p>

Scikit-Optimize on Ubuntu 26.04 with Maintenance Support (kCloud) is a lightweight machine learning optimization framework, repackaged by kCloud with operational support included for scalable AI workflows.

</p>

<h3>Key Features</h3>

<ul>

<li>Bayesian optimization and sequential model-based optimization</li>

<li>Integration with Scikit-learn workflows</li>

<li>Supports hyperparameter tuning and optimization tasks</li>

<li>Quick deployment on AWS EC2 via AMI</li>

<li>Production-ready environment for ML experimentation</li>

</ul>

<h3>Supporting Version</h3>

<ul>

<li>Latest Scikit-Optimize version</li>

</ul>

<h3>AWS Marketplace Setup</h3>

<ul>

<li>Ready-to-use EC2 AMI</li>

<li>Billing handled through AWS</li>

</ul>

<h3>Help Options</h3>

<p>Optional kCloud assistance.</p>

Highlights

Highlighted by the publisher on AWS Marketplace.

Sequential model-based optimization support

Bayesian optimization for machine learning workflows

Hyperparameter tuning for Scikit-learn models

Agent build and provenance

See the full provenance

The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.

Plans and pricing as listed

21 listed
m4.large
  • Hrs
$0.10
t3.micro
  • Hrs
$0.10
t2.micro
  • Hrs
$0.001
t2.large
  • Hrs
$0.10
r4.large
  • Hrs
$0.10
r3.large
  • Hrs
$0.10
t3.large
  • Hrs
$0.10
t3.nano
  • Hrs
$0.10
t2.2xlarge
  • Hrs
$0.10
t2.medium
  • Hrs
$0.10
t3.medium
  • Hrs
$0.10
t3.small
  • Hrs
$0.10
and 9 more plans on the listing

Refund terms

As stated by the publisher on AWS Marketplace.

No refund

Sources

Marketplace listingaws.amazon.comSource
App certificationaws.amazon.comSource
StandardEulaStandardEulaSource

Linked repositories

RepositoriesUnknownUnknown

Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.

Pricing
Paid
21 plans listed
Delivery
Virtual machine
"Feel free to reach out anytime. Our support team is available 24x7 for assistance mail: meha@kcloudhubs.com"
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