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Jupyter Hub for Deep Learning using Python packaged by Data Science Dojo

Data Science Dojo · Intelligence & Research

Virtual MachinesNo attestation published

Certification per Microsoft Marketplace.

Provenance reach3 of 12 layers traced

Evidence tier Source Confirmed · 9 captures on record

User ratingNot rated0 reviews on the listing
Runs onVirtual MachinesVirtual machine
ProvenanceUnknown33% 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 Microsoft Marketplace.

Data Science Dojo delivers data science education, consulting, and technical services to harvest the power of data.

Trademarks: This software listing is packaged by Data Science Dojo. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

Show the rest of the publisher’s description (48 more lines)

About the offer:

Jupyter Hub for Deep Learning using Python gives you an effortless coding environment in the cloud with pre-installed Deep Learning python libraries, which reduces the burden of installation and maintenance of tasks. Through this offer, a user can work on different applications of Deep Learning including self driving cars, healthcare, fraud detection, language translations,auto-compeletion of sentences, photo descriptions, image coloring and captioning, object detection and localization. The heavy computations required for these applications are not performed on the user's local machine. Instead, They are performed in the Azure cloud, which increases responsiveness and processing speed.

Who benefits from this offer:

  • Teams of developers
  • Data scientists
  • Machine learning engineers
  • Scientific researcher groups
  • And anyone else interested in data science tools

What is included in this offer:

  • Pre-installed Python libraries and packages for Deep Learning`.
  • Ready to go notebooks which consist of example codes through which user can get guidance for working on Deep Learning applications.
  • Code consoles to run code interactively, with full support for rich output.
  • Kernel-backed documents enable code in any text file (Markdown, Python, etc.) to be run interactively in Jupyter kernel.
  • Work with multiple notebooks at the same time.

Technical Specifications:

  • Minimum Recommended memory: 56GB RAM
  • Minimum Recommended vCPU: 6 vCPUs
  • Operating System: Ubuntu 20.04
  • GPU required

Following Authoring Tools are supported in this offer:

  • JupyterHub
  • Jupyter Lab
  • Terminal

Our instance supports following Python deep learning libraries:

  • Numpy
  • Matplotlib
  • Pandas
  • Seaborn
  • Tensorflow
  • Tflearn
  • PyTorch
  • Keras
  • Scikit Learn
  • Lasagne
  • Leather
  • Theano
  • D2L
  • OpenCV

Our offer provides repositories from following sources:

  • Github repository of book Deep Learning with Python 2nd Edition, by author François Chollet.
  • Github repository of book Hands On Deep Learning Algorithms with Python, by author Sudharsan Ravichandiran.
  • Github repository of book Hands on Machine Learning with ScikitLearn Keras and TensorFlow, by author Geron Aurelien.
  • Github repository of collection on Deep Learning Models, by author Sebastian Raschka.

The default HTTP port JupyterHub listen to is 8000. You can access the web interface at http://yourip:8000

Use following credentials:

  • Username: guest
  • Password: guest@123

The Jupyter Trademark is registered with the U.S. Patent & Trademark Office.

Preview

5 images
Jupyter Hub for Deep Learning using Python packaged by Data Science Dojo preview 1Jupyter Hub for Deep Learning using Python packaged by Data Science Dojo preview 2Jupyter Hub for Deep Learning using Python packaged by Data Science Dojo preview 3Jupyter Hub for Deep Learning using Python packaged by Data Science Dojo preview 4Jupyter Hub for Deep Learning using Python packaged by Data Science Dojo preview 5

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.

Compliance

Government
  • FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27

Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.

Vendor

External enrichment · as of 2026-07-09

CompanyHubSpot, Inc.Automated
HQUnited States of AmericaAutomated
IndustryTechnologyAutomated
Websitehttps://www.hubspot.com/

Sources

Marketplace listingmarketplace.microsoft.comSource
Privacy PolicyPrivacy PolicySource
License TermsLicense TermsSource

Publisher resources

6 links
Supporthubs.laSource
What Is Deep Learning?www.youtube.comSource
Keras with TensorFlowwww.youtube.comSource
PyTorch for Deep Learningwww.youtube.comSource
Deep Learning Applicationswww.youtube.comSource
JupyterHub Tutorial: Set up your Lab, Classroom, or Businesswww.youtube.comSource

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
Unknown
Not stated
Delivery
Virtual machine
https://hubs.la/Q01b335M0
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