Paperspace Gradient VS Scale Nucleus

Paperspace Gradient

A Linux desktop in the cloud built for Machine Learning

Scale Nucleus

The mission control for your ML data

Landing page //
2023-02-04

Landing page //
2023-08-20

Paperspace for Machine Learning

Scale Nucleus videos

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Using Scale Nucleus & Rapid to Label New Datasets Efficiently

Category Popularity

0-100% (relative to Paperspace Gradient and Scale Nucleus)

Scale Nucleus

AI

49 49%

AI

51% 51

Developer Tools

35 35%

Developer Tools

65% 65

Data Science And Machine Learning

100 100%

Data Science And Machine Learning

0% 0

APIs

0 0%

APIs

100% 100

User comments

Share your experience with using Paperspace Gradient and Scale Nucleus. For example, how are they different and which one is better?

Reviews

These are some of the external sources and on-site user reviews we've used to compare Paperspace Gradient and Scale Nucleus

Gradient by Paperspace is a robust alternative that allows developing, training, and deploying machine learning models quickly. With free GPU tier and one-click Jupyter notebooks, it's an easy-to-use platform that doesn't compromise on functionality. Gradient is also known for its powerful experiment tracking and version control capabilities.

Source: deepnote.com

12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing

Paperspace Gradient is a cloud-based platform for data science and machine learning that offers many of the same features as Jupyter Notebooks, as well as a number of additional capabilities. It provides powerful hardware resources, including GPUs, and supports Python, R, and Julia.

Source: noteable.io

Scale Nucleus Reviews

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Social recommendations and mentions

Based on our record, Scale Nucleus should be more popular than Paperspace Gradient. 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.

Paperspace Gradient mentions (1)

JetBrains announced a new Data Science platform for teams
Yeah, seems so to me. Add it to the list. https://cloud.google.com/notebooks https://notebooks.azure.com/ https://aws.amazon.com/emr/features/notebooks https://colab.research.google.com/ https://www.kaggle.com/code https://gradient.paperspace.com/. - Source: Hacker News / almost 3 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