Amazon SageMaker

By Amazon SageMaker

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What is Amazon SageMaker?

Amazon SageMaker is a fully managed machine learning (ML) service on AWS that empowers developers and data scientists to construct, prepare, and deploy machine learning models in a short amount of time. Using AWS SageMaker, it is possible to simplify the overall ML process and run models in a SageMaker endpoint to make predictions in real-time.

Pricing of Amazon SageMaker

Amazon SageMaker

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Amazon SageMaker Studio notebooks
On-demand notebook instances: 250 hours of ml.t3.medium instance on Studio notebooks OR 250 hours of ml.t2 medium instance or ml.t3.medium instance on on-demand notebook instances
Amazon SageMaker Data Wrangler: 25 hours of ml.m5.4xlarge instance
Amazon SageMaker Feature Store: 10M write units
10M read units
25 GB storage
Training: 50 hours of m4.xlarge or m5.xlarge instances
Inference: 125 hours of m4.xlarge or m5.xlarge instances
Amazon SageMaker Studio no

Key Specification

Other Categories:	New Saas Software Data Management Software Data Labeling Software Data Annotation Software
Deployment:	Cloud Hosted
Customer Support:	Online (Ticket)
Customization:	No
Languages Support:	English

Who uses Amazon SageMaker

SMEs

Enterprises

Company Details

Company Name:	Amazon SageMaker
Headquarter:	NA,
Social Media:

Amazon SageMaker Description

Why Choose Amazon SageMaker?

When selecting Amazon SageMaker, one has to use a scalable and secure Amazon AWS Sage ML platform. It simplifies the task of running infrastructure, enables more rapid experimentation, and offers combined monitoring and deployment tools of models.

Advantages of Amazon SageMaker.

Accelerated Model Deployment: Rapidly deploy models to an endpoint on SageMaker.
Fully Managed Service: There is no reason to deal with servers; AWS SageMaker takes care of it.
Scalability: ML workloads can easily be upscaled or downscaled.
Integration with AWS Ecosystem: Smoothly integrates with the rest of the AWS Sages services.
Economical: Only pay on a per-use basis.

How to Use Amazon SageMaker

Clean your data and put it into AWS SageMaker.
Machine learning Build and train your machine learning model with built-in algorithms or own code.
Trained model Deploy your trained model to a SageMaker endpoint.
Test, monitor and optimize your model performance.

Amazon SageMaker Features.

Studio IDE: ML development in a single package.
Built-in Algorithms: Built-in Algorithms represent ready created algorithms to train faster models.
SageMaker Endpoint: Real time inference on production workloads.
Automatic Model Optimization: Hyperparameter optimization.
Security & Compliance: AWS inbuilt security.

Amazon SageMaker Demo

Have a preview of the power of AWS SageMaker through a demo trial and experience how fast you can train, deploy, and manage ML models through a SageMaker endpoint.

Amazon SageMaker Pricing

The pricing is also dynamic and is based on the calculate, storage, and the utilization of the AWS SageMaker services, such as model training and SageMaker endpoints.

Pricing by Contact Techimply.