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AWS SageMaker Ground Truth VS Apple Core ML

Compare AWS SageMaker Ground Truth VS Apple Core ML and see what are their differences

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AWS SageMaker Ground Truth logo AWS SageMaker Ground Truth

Build highly accurate training datasets using machine learning and reduce data labeling costs by up to 70%.

Apple Core ML logo Apple Core ML

Integrate a broad variety of ML model types into your app
  • AWS SageMaker Ground Truth Landing page
    Landing page //
    2023-04-14
  • Apple Core ML Landing page
    Landing page //
    2023-06-13

AWS SageMaker Ground Truth videos

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Apple Core ML videos

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IBM Watson & Apple Core ML Collaboration - What it means for app development

Category Popularity

0-100% (relative to AWS SageMaker Ground Truth and Apple Core ML)

AWS SageMaker Ground Truth

Apple Core ML

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
AI
59 59%
AI
41% 41
Data Labeling
100 100%
Data Labeling
0% 0

User comments

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Social recommendations and mentions

Based on our record, Apple Core ML should be more popular than AWS SageMaker Ground Truth. It has been mentiond 7 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.

AWS SageMaker Ground Truth mentions (3)

  • [D] What are people using to organize large groups of people for data labelling?
    Perhaps https://aws.amazon.com/sagemaker/data-labeling/ ? Source: almost 2 years ago
  • Top 5 AWS ML Sessions to Attend at AWS re:Invent 2021
    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 complete data-preparation workflow, including how to use SageMaker Ground Truth to label training datasets, as well as how to extract data from numerous data sources, convert it using... - Source: dev.to / over 2 years ago
  • Blocked by MLData…it was only a matter of time
    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, Amazon just redirect the labeling job for us using and requester account in mTurk, that explains why the communication is unacceptable with this requester. Source: over 2 years ago

Apple Core ML mentions (7)

  • Ask HN: Where is Apple? They seem to be left out of the AI race?
    On the machine learning side of AI, they have CoreML. You can drag-and-drop images into Xcode to train an image classifier. And run the models on device, so if solar flares destroy the cell phone network and terrorists bomb all the data centers, your phone could still tell you if it's a hot dog or not. https://developer.apple.com/machine-learning/ https://developer.apple.com/machine-learning/core-ml/... - Source: Hacker News / 4 months ago
  • The Magnitude of the AI Bubble
    Apple has actually created ML chipsets, so AI can be executed natively, on-device. https://developer.apple.com/machine-learning/. - Source: Hacker News / 5 months ago
  • Does anyone else suspect that the official iOS ChatGPT app might be conducting some local inference / edge-computing? [Discussion]
    For your reference, Apple's pages for Machine Learning for Developers and for their research. The Apple Neural Engine was custom designed to work better with their proprietary machine learning programs -- and they've been opening up access to developers by extending support / compatibility for TensorFlow and PyTorch. They've also got CoreML, CreateML, and various APIs they are making to allow more use of their... Source: about 1 year ago
  • Apple to occupy 90% of TSMC 3nm capacity in 2023
    > It’d be one thing if Apple actually worked on AI softwares a bit and made it readily available to developers. * Apple Silicon CPUs have a Neural Engine specifically made for fast ML-inference * Apple supports PyTorch (https://developer.apple.com/metal/pytorch/) * Apple has its own easily accessible machine-learning framework called Core-ML (https://developer.apple.com/machine-learning/) So it would be inaccurate... - Source: Hacker News / about 1 year ago
  • The iPhone 13 is a pitch-perfect iPhone 12S
    This is the developer documentation where they advertise the APIs - https://developer.apple.com/machine-learning/. Source: almost 3 years ago
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What are some alternatives?

When comparing AWS SageMaker Ground Truth and Apple Core ML, you can also consider the following products

Computer Vision Annotation Tool (CVAT) - Powerful and efficient Computer Vision Annotation Tool (CVAT) - opencv/cvat

Amazon Machine Learning - Machine learning made easy for developers of any skill level

Labelbox - Build computer vision products for the real world

TensorFlow Lite - Low-latency inference of on-device ML models

Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...

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

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