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What is the primary function of Amazon SageMaker Training Jobs?
A
To manage model lineage and versioning
B
To run distributed training workloads on managed compute resources
C
To host notebooks for experimentation
D
To convert models into edge-optimized formats
Explanation:
Amazon SageMaker Training Jobs is specifically designed for training machine learning models on AWS infrastructure. Here's why option B is correct:
Key Features of SageMaker Training Jobs:
Managed Compute Resources: SageMaker automatically provisions and manages the compute instances needed for training
Distributed Training: Supports distributed training across multiple instances for large-scale models
Automatic Scaling: Scales compute resources based on the training workload
Built-in Algorithms: Provides optimized implementations of popular ML algorithms
Custom Containers: Allows using custom Docker containers for specialized training needs
Why other options are incorrect:
Option A: Model lineage and versioning is handled by SageMaker Model Registry
Option C: Notebook hosting is provided by SageMaker Studio Notebooks or SageMaker Notebook Instances
Option D: Converting models to edge-optimized formats is done by SageMaker Neo
Use Cases for SageMaker Training Jobs:
Training deep learning models on GPU instances
Distributed training across multiple nodes
Hyperparameter tuning experiments
Batch transform jobs for inference
This service abstracts away the infrastructure management, allowing data scientists to focus on model development rather than infrastructure setup.