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gptkbp:instance_of
|
gptkb:software
|
|
gptkbp:built
|
AWS infrastructure
|
|
gptkbp:can_be_combined_with
|
gptkb:Amazon_Sage_Maker_Debugger
gptkb:Amazon_Sage_Maker_Model_Monitor
|
|
gptkbp:can_be_used_for
|
Deep learning
Machine learning
|
|
gptkbp:developed_by
|
gptkb:Amazon_Web_Services
|
|
gptkbp:enables
|
Mixed precision training
|
|
gptkbp:enhances
|
Model training efficiency
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Amazon Sage Maker Training Compiler
|
|
gptkbp:improves
|
Training performance
|
|
gptkbp:integrates_with
|
gptkb:Sage
|
|
gptkbp:is_accessible_by
|
gptkb:AWS_SDKs
gptkb:AWS_Management_Console
gptkb:AWS_CLI
|
|
gptkbp:is_available_in
|
Multiple regions
|
|
gptkbp:is_available_on
|
gptkb:AWS_Marketplace
|
|
gptkbp:is_compatible_with
|
gptkb:AWS_Inferentia
gptkb:NVIDIA_GPUs
|
|
gptkbp:is_designed_for
|
Data scientists
Machine learning engineers
|
|
gptkbp:is_effective_against
|
gptkb:Yes
|
|
gptkbp:is_optimized_for
|
Memory usage
Cloud environments
|
|
gptkbp:is_part_of
|
AWS AI services
Machine learning workflow
AI/ ML ecosystem
Amazon Sage Maker suite
|
|
gptkbp:is_scalable
|
Large datasets
|
|
gptkbp:is_supported_by
|
AWS documentation
Community forums
|
|
gptkbp:is_updated_by
|
gptkb:Yes
|
|
gptkbp:is_used_for
|
Model evaluation
|
|
gptkbp:is_used_in
|
gptkb:research
Industry applications
|
|
gptkbp:offers
|
Custom training scripts
|
|
gptkbp:provides
|
User-friendly interface
Logging and monitoring features
Integration with Jupyter notebooks
Performance profiling
Automatic optimization
|
|
gptkbp:purpose
|
Optimize training of machine learning models
|
|
gptkbp:reduces
|
Training costs
Training time
|
|
gptkbp:security
|
gptkb:Yes
|
|
gptkbp:suitable_for
|
Enterprises
Startups
|
|
gptkbp:supports
|
gptkb:Tensor_Flow
gptkb:Py_Torch
Hyperparameter tuning
Real-time inference
Distributed training
Batch training
|
|
gptkbp:uses
|
Graph optimization techniques
|
|
gptkbp:bfsParent
|
gptkb:Amazon_Web_Services_AI
|
|
gptkbp:bfsLayer
|
5
|