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Design Research Technique VS Scale Nucleus

Compare Design Research Technique VS Scale Nucleus and see what are their differences

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

Design Research Technique logo Design Research Technique

Huge repository of design techniques for every project stage

Scale Nucleus logo Scale Nucleus

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

Design Research Technique videos

No Design Research Technique 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 Design Research Technique and Scale Nucleus)

Design Research Technique

Scale Nucleus

Productivity
100 100%
Productivity
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Design Tools
100 100%
Design Tools
0% 0
AI
0 0%
AI
100% 100

User comments

Share your experience with using Design Research Technique 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 seems to be more popular. 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.

Design Research Technique mentions (0)

We have not tracked any mentions of Design Research Technique yet. Tracking of Design Research Technique recommendations started around Mar 2021.

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 Design Research Technique and Scale Nucleus, you can also consider the following products

Sourceful - A search engine for publicly-sourced Google docs

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

SatisMeter + NomNom - Turn your SatisMeter NPS responses into product insights

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

CareKit by Apple - Open source software framework for creating health apps

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

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