+
+

Related Products

  • RunPod
    205 Ratings
    Visit Website
  • Vertex AI
    827 Ratings
    Visit Website
  • LM-Kit.NET
    24 Ratings
    Visit Website
  • Google AI Studio
    11 Ratings
    Visit Website
  • Qloo
    23 Ratings
    Visit Website
  • Teradata VantageCloud
    992 Ratings
    Visit Website
  • Google Cloud BigQuery
    1,939 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • Sage Intacct
    7,935 Ratings
    Visit Website
  • Google Compute Engine
    1,155 Ratings
    Visit Website

About

Amazon SageMaker makes it easy to deploy ML models to make predictions (also known as inference) at the best price-performance for any use case. It provides a broad selection of ML infrastructure and model deployment options to help meet all your ML inference needs. It is a fully managed service and integrates with MLOps tools, so you can scale your model deployment, reduce inference costs, manage models more effectively in production, and reduce operational burden. From low latency (a few milliseconds) and high throughput (hundreds of thousands of requests per second) to long-running inference for use cases such as natural language processing and computer vision, you can use Amazon SageMaker for all your inference needs.

About

Using Amazon SageMaker Pipelines, you can create ML workflows with an easy-to-use Python SDK, and then visualize and manage your workflow using Amazon SageMaker Studio. You can be more efficient and scale faster by storing and reusing the workflow steps you create in SageMaker Pipelines. You can also get started quickly with built-in templates to build, test, register, and deploy models so you can get started with CI/CD in your ML environment quickly. Many customers have hundreds of workflows, each with a different version of the same model. With the SageMaker Pipelines model registry, you can track these versions in a central repository where it is easy to choose the right model for deployment based on your business requirements. You can use SageMaker Studio to browse and discover models, or you can access them through the SageMaker Python SDK.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Companies looking for a powerful Machine Learning solution

Audience

Individuals that need a first purpose-built CI/CD service for machine learning

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

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

Company Information

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

Alternatives

Alternatives

Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth

Amazon Web Services

Categories

Categories

Integrations

Amazon SageMaker
Amazon Web Services (AWS)

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Claim Amazon SageMaker Model Deployment and update features and information
Claim Amazon SageMaker Model Deployment and update features and information
Claim Amazon SageMaker Pipelines and update features and information
Claim Amazon SageMaker Pipelines and update features and information