
Build, train, and deploy ML models at scale on AWS
Visit WebsiteWhat is Amazon SageMaker?
Amazon SageMaker is a hosting & deployment tool. SageMaker provides everything needed to build, train, and deploy machine learning models on AWS. Jupyter notebooks for experimentation, managed training infrastructure, one-click deployment to production endpoints. The platform handles the infrastructure complexity that usually slows ML projects. Amazon SageMaker is paid-only, with most plans including a trial period. Buyers most often compare Amazon SageMaker against MLflow, Google Cloud, Together AI.
TL;DR - Amazon SageMaker
- Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models
- It provides notebooks, training infrastructure, and one-click deployment with built-in algorithms
- Pay for compute and storage used, with free tier covering 250 hours of notebook usage
Pros & Cons
Pros
- Complete ML platform
- Jupyter notebooks
- Training at scale
- Model deployment
- Feature store
Cons
- Expensive
- Complex
- Learning curve
- Vendor lock-in
- Overkill for simple ML
Ratings Across the Web
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Key Features
Pricing Plans
Free TrialFree Tier
Usage-based pricing
- 250 hrs notebooks
- 50 hrs training
- 125 hrs hosting
- ml.t3.medium
On-Demand
$0.23/hour
ml.m5.xlarge training
- All instance types
- Pay for usage
- No commitment
- All features
Savings Plans
Custom
1-3 year terms
- Up to 64% savings
- Flexible instances
- All components
About Amazon SageMaker
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Source: aws.amazon.com