
Scale Nucleus
ML Image Classifier
Aquarium
Prodigy
mlblocks
PerceptiLabs
Machine Learning Playground
Roboflow Universe
OpenShift
Google App Engine
Salesforce Platform
Dokku
Heroku
Google Cloud Functions
Microsoft Azure
Kubernetes
Scale Nucleus
OpenShiftBased 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.
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 4 years ago
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: about 5 years ago
ML Image Classifier - Quickly train custom machine learning models in your browser
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
Aquarium - Improve ML models by improving datasets theyโre trained on
Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.
Prodigy - Radically efficient machine teaching
Dokku - Docker powered mini-Heroku in around 100 lines of Bash