Software Alternatives & Reviews

ML Image Classifier VS Scale Nucleus

Compare ML Image Classifier VS Scale Nucleus and see what are their differences

ML Image Classifier logo ML Image Classifier

Quickly train custom machine learning models in your browser

Scale Nucleus logo Scale Nucleus

The mission control for your ML data
  • ML Image Classifier Landing page
    Landing page //
    2019-07-02
  • Scale Nucleus Landing page
    Landing page //
    2023-08-20

ML Image Classifier videos

No ML Image Classifier videos yet. You could help us improve this page by suggesting one.

+ Add video

Scale Nucleus videos

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 ML Image Classifier and Scale Nucleus)
Developer Tools
47 47%
53% 53
AI
47 47%
53% 53
Tech
100 100%
0% 0
APIs
46 46%
54% 54

User comments

Share your experience with using ML Image Classifier and Scale Nucleus. For example, how are they different and which one is better?
Log in or Post with

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.

ML Image Classifier mentions (0)

We have not tracked any mentions of ML Image Classifier yet. Tracking of ML Image Classifier 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 ML Image Classifier and Scale Nucleus, you can also consider the following products

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

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

Pretrained AI - Integrate pretrained machine learning models in minutes.

Google Cloud TPUs - Build and train machine learning models with Google

Curator - The visual notes app, now on iPhone!

Roboflow Universe - You no longer need to collect and label images or train a ML model to add computer vision to your project.