
Qubole
Scikit-learn
Labelbox
BigML
machine-learning in Python
Microsoft Recommendations API
Google CLOUD AUTOML
Build highly accurate training datasets using machine learning and reduce data labeling costs by up to 70%.

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Which is more popular?
Based on our record, AWS SageMaker Ground Truth seems to be more popular. It has been mentioned 3 times since March 2021.
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| Website | aws.amazon.com | opalstack.com |
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Share your experience with using AWS SageMaker Ground Truth and Opalstack. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


Perhaps https://aws.amazon.com/sagemaker/data-labeling/ ? Source: about 4 years ago
In this session you will discover how to use Amazon SageMaker to prepare data for machine learning in minutes. SageMaker provides data preparation tools that make it easier to label, prepare, and analyse your data. Walk through a... - Source: dev.to / almost 5 years ago
As for who run MLD I guess It’s Amazon itself, have a look at this https://aws.amazon.com/sagemaker/groundtruth/. I speculate that multiple companies use this resource and they are the one responsible to upload the correct instructions,... Source: almost 5 years ago
Tracking Opalstack since Sep 2023.
When comparing AWS SageMaker Ground Truth and Opalstack, you can also consider the following products.

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
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scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
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Build computer vision products for the real world
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BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
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Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.
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Obtains details of a cached recommendation.
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