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sttr VS Scale Nucleus

Compare sttr VS Scale Nucleus and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

sttr logo sttr

sttr is command-line software that allows you to quickly run various transformation operations on the string.

Scale Nucleus logo Scale Nucleus

The mission control for your ML data
  • sttr Landing page
    Landing page //
    2023-09-12
  • Scale Nucleus Landing page
    Landing page //
    2023-08-20

sttr videos

No sttr videos yet. You could help us improve this page by suggesting one.

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Scale Nucleus videos

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Using Scale Nucleus & Rapid to Label New Datasets Efficiently

More videos:

  • Review - Scale Nucleus: Send to Annotation
  • Review - Scale Nucleus: Find Missing Annotations

Category Popularity

0-100% (relative to sttr and Scale Nucleus)

sttr

Scale Nucleus

Productivity
100 100%
Productivity
0% 0
Developer Tools
20 20%
Developer Tools
80% 80
AI
0 0%
AI
100% 100
Open Source
100 100%
Open Source
0% 0

User comments

Share your experience with using sttr and Scale Nucleus. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Scale Nucleus should be more popular than sttr. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

sttr mentions (1)

  • CyberChef – The Cyber Swiss Army Knife
    It's having both TUI as well as CLI modes. https://github.com/abhimanyu003/sttr Since it's written in GO, you can run it pretty much anywhere you like :) ( cross platform ) Yes, it support file inputs as well. - Source: Hacker News / over 2 years ago

Scale Nucleus mentions (2)

  • [Discussion] The most painful thing about machine learning
    At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago
  • Unit Testing for Production ML Workflows?
    To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 years ago

What are some alternatives?

When comparing sttr and Scale Nucleus, you can also consider the following products

Approve-CI - A continuous integration tool monitoring code reviews.

PerceptiLabs - A tool to build your machine learning model at warp speed.

Todo for hackers - CLI Todo app for hackers

Aquarium - Improve ML models by improving datasets they’re trained on

Approve app for Zendesk - Any enforceable and auditable approval workflow for Zendesk tickets you can imagine can be easily created using the Approve app.

ML Image Classifier - Quickly train custom machine learning models in your browser

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