Home/Compare/amazon-sagemaker-examples vs geti_v2

Comparison

amazon-sagemaker-examples vs geti_v2

Verdict

Pick amazon-sagemaker-examples if jupyter notebooks for illustrating machine learning workflows on Amazon SageMaker; pick geti_v2 if geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with frameworks like OpenVINO.

Markdown twin · amazon-sagemaker-examples alternatives · geti_v2 alternatives

GraphCanon updated Sep 20, 2026

10views this month

amazon-sagemaker-examples logo

amazon-sagemaker-examples

aws/amazon-sagemaker-examples

11kpushed Sep 9, 2026
vs
geti_v2 logo

geti_v2

open-edge-platform/geti_v2

483pushed Jul 30, 2026

Trust & integrity

Signalamazon-sagemaker-examplesgeti_v2
Maintenance
Active (10d since push)
As of Sep 20, 2026 · github_public_v1
Archived (51d since push)
As of Sep 19, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 20, 2026 · github_public_v1
Not a fork · Organization account
As of Sep 19, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 15, 2026 · osv@v1
No lockfile (source not queried)
As of Jul 11, 2026 · 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

amazon-sagemaker-examples
Jupyter notebooks for building, training, and deploying ML models using Amazon SageMaker
geti_v2
Build computer vision models quickly with less data

Stars

amazon-sagemaker-examples
11k
geti_v2
483

Forks

amazon-sagemaker-examples
7.0k
geti_v2
51

Open issues

amazon-sagemaker-examples
854
geti_v2
87

Language

amazon-sagemaker-examples
Jupyter Notebook
geti_v2
TypeScript

Adopt for

amazon-sagemaker-examples
Jupyter notebooks for illustrating machine learning workflows on Amazon SageMaker
geti_v2
geti_v2 is designed for developers who need to build computer vision models quickly using limited datasets. It supports TypeScript and integrates with frameworks like OpenVINO.

Persona

amazon-sagemaker-examples
-
geti_v2
-

Runtime

amazon-sagemaker-examples
-
geti_v2
-

License

amazon-sagemaker-examples
Apache-2.0, allowing free use for any purpose with conditions on attribution and license preservation
geti_v2
The licensing type is listed as 'Other', implying that the license details should be closely reviewed for specific terms.

Last pushed

amazon-sagemaker-examples
Sep 9, 2026
geti_v2
Jul 30, 2026

Categories

amazon-sagemaker-examples
Inference & Serving, Model Training
geti_v2
Computer Vision, Inference & Serving, Model Training

Trust and health

Maintenance

amazon-sagemaker-examples
Active (82%)
geti_v2
Archived (8%)

Days since push

amazon-sagemaker-examples
10d
geti_v2
51d

Archived on GitHub

amazon-sagemaker-examples
No
geti_v2
Yes

Open issues (now)

amazon-sagemaker-examples
854
geti_v2
87

Stars delta

amazon-sagemaker-examples
+6 (30d)
geti_v2
-1 (30d)

Open issues delta

amazon-sagemaker-examples
+5 (30d)
geti_v2
+1 (30d)

Full report

amazon-sagemaker-examples
Trust report

Choose amazon-sagemaker-examples if…

  • amazon-sagemaker-examples is primarily Jupyter Notebook; geti_v2 is TypeScript.
  • License: amazon-sagemaker-examples is Apache-2.0, geti_v2 is Other.
  • Tags unique to amazon-sagemaker-examples: aws, data-science, jupyter-notebook, machine-learning.
  • When you need examples specific to building models with Amazon SageMaker

When NOT to use amazon-sagemaker-examples

  • For non-AWS environments where cost and integration complexities could outweigh benefits
  • If seeking open-source tools without ties to a single cloud provider

Choose geti_v2 if…

  • geti_v2 is primarily TypeScript; amazon-sagemaker-examples is Jupyter Notebook.
  • License: geti_v2 is Other, amazon-sagemaker-examples is Apache-2.0.
  • Pricing: Pricing information is not provided..
  • Requirements: Min 0 GB RAM.
  • Tags unique to geti_v2: computer-vision, fine-tuning.
  • Also covers Computer Vision.
  • When you have a shortage of labeled data but still require high accuracy in your computer vision model.

When NOT to use geti_v2

  • When you need to work with languages other than TypeScript, as geti_v2 is specifically designed for use with TypeScript environments.
  • In scenarios where you have abundant labeled data and can afford longer training times, which may not leverage the key advantage of geti_v2's efficiency in low-data conditions.

Explore

Sources

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

GitHub stars on cards: amazon-sagemaker-examples 11k · geti_v2 483 (synced Sep 20, 2026).

Common questions

What is the difference between amazon-sagemaker-examples and geti_v2?
amazon-sagemaker-examples: Jupyter notebooks for building, training, and deploying ML models using Amazon SageMaker. geti_v2: Build computer vision models quickly with less data. See the comparison table for live GitHub stats and shared categories.
When should I choose amazon-sagemaker-examples over geti_v2?
Choose amazon-sagemaker-examples over geti_v2 when amazon-sagemaker-examples is primarily Jupyter Notebook; geti_v2 is TypeScript; License: amazon-sagemaker-examples is Apache-2.0, geti_v2 is Other; Tags unique to amazon-sagemaker-examples: aws, data-science, jupyter-notebook, machine-learning; When you need examples specific to building models with Amazon SageMaker.
When should I choose geti_v2 over amazon-sagemaker-examples?
Choose geti_v2 over amazon-sagemaker-examples when geti_v2 is primarily TypeScript; amazon-sagemaker-examples is Jupyter Notebook; License: geti_v2 is Other, amazon-sagemaker-examples is Apache-2.0; Pricing: Pricing information is not provided.; Requirements: Min 0 GB RAM; Tags unique to geti_v2: computer-vision, fine-tuning; Also covers Computer Vision; When you have a shortage of labeled data but still require high accuracy in your computer vision model.
When should I avoid amazon-sagemaker-examples?
For non-AWS environments where cost and integration complexities could outweigh benefits If seeking open-source tools without ties to a single cloud provider
When should I avoid geti_v2?
When you need to work with languages other than TypeScript, as geti_v2 is specifically designed for use with TypeScript environments. In scenarios where you have abundant labeled data and can afford longer training times, which may not leverage the key advantage of geti_v2's efficiency in low-data conditions.
Is amazon-sagemaker-examples or geti_v2 more popular on GitHub?
amazon-sagemaker-examples has more GitHub stars (10,990 vs 483). Stars measure visibility, not whether either tool fits your constraints.
Are amazon-sagemaker-examples and geti_v2 open source?
Yes - both are open-source projects on GitHub (amazon-sagemaker-examples: Apache-2.0, geti_v2: Other).
Where can I find alternatives to amazon-sagemaker-examples or geti_v2?
GraphCanon lists graph-backed alternatives at amazon-sagemaker-examples alternatives and geti_v2 alternatives (amazon-sagemaker-examples markdown twin, geti_v2 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, amazon-sagemaker-examples or geti_v2?
amazon-sagemaker-examples: Active. geti_v2: Archived. 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 amazon-sagemaker-examples and geti_v2?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: amazon-sagemaker-examples trust report; geti_v2 trust report.

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