Audience

Companies looking for a Machine learning hub solution that has built-in algorithms, foundation models

About Amazon SageMaker JumpStart

Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. With SageMaker JumpStart, you can access built-in algorithms with pretrained models from model hubs, pretrained foundation models to help you perform tasks such as article summarization and image generation, and prebuilt solutions to solve common use cases. In addition, you can share ML artifacts, including ML models and notebooks, within your organization to accelerate ML model building and deployment. SageMaker JumpStart provides hundreds of built-in algorithms with pretrained models from model hubs, including TensorFlow Hub, PyTorch Hub, HuggingFace, and MxNet GluonCV. You can also access built-in algorithms using the SageMaker Python SDK. Built-in algorithms cover common ML tasks, such as data classifications (image, text, tabular) and sentiment analysis.

Integrations

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Company Information

Amazon
Founded: 2006
United States
aws.amazon.com/sagemaker/jumpstart/

Videos and Screen Captures

Amazon SageMaker JumpStart Screenshot 1
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Product Details

Platforms Supported
Cloud
Training
Documentation
Support
Online

Amazon SageMaker JumpStart Frequently Asked Questions

Q: What kinds of users and organization types does Amazon SageMaker JumpStart work with?
Q: What languages does Amazon SageMaker JumpStart support in their product?
Q: What kind of support options does Amazon SageMaker JumpStart offer?
Q: What other applications or services does Amazon SageMaker JumpStart integrate with?
Q: What type of training does Amazon SageMaker JumpStart provide?

Amazon SageMaker JumpStart Product Features

Machine Learning

Deep Learning Not Supported
ML Algorithm Library Not Supported
Model Training Not Supported
Natural Language Processing (NLP) Not Supported
Predictive Modeling Not Supported
Templates Not Supported
Visualization Not Supported
Statistical / Mathematical Tools Not Supported