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gptkbp:instanceOf
|
gptkb:software
|
|
gptkbp:developedBy
|
gptkb:Amazon
|
|
gptkbp:documentation
|
https://sagemaker.readthedocs.io/
|
|
gptkbp:enables
|
hyperparameter tuning
model monitoring
endpoint deployment
batch transform
pipeline automation
training jobs
|
|
gptkbp:firstReleased
|
2017
|
|
gptkbp:integratesWith
|
gptkb:Amazon_SageMaker
|
|
gptkbp:latestReleaseVersion
|
2.x
|
|
gptkbp:license
|
gptkb:Apache_License_2.0
|
|
gptkbp:npmPackage
|
sagemaker
|
|
gptkbp:platform
|
gptkb:TensorFlow
gptkb:XGBoost
gptkb:Amazon_Web_Services
gptkb:MXNet
gptkb:PyTorch
gptkb:Scikit-learn
gptkb:Hugging_Face_Transformers
|
|
gptkbp:programmingLanguage
|
gptkb:Python
|
|
gptkbp:repository
|
https://github.com/aws/sagemaker-python-sdk
|
|
gptkbp:supports
|
gptkb:Jupyter_Notebook
gptkb:Amazon_SageMaker_Studio
custom Docker containers
Bring Your Own Model (BYOM)
|
|
gptkbp:usedFor
|
gptkb:machine_learning
model deployment
model inference
model training
|
|
gptkbp:bfsParent
|
gptkb:SageMaker_Studio_Model_Pipelines
gptkb:SageMaker_Studio_Model_Profiler_Integration
gptkb:SageMaker_Studio_Model_Registry
gptkb:SageMaker_Experiments
gptkb:SageMaker_Inference_Recommender
gptkb:SageMaker_Model_Monitor
gptkb:Amazon_SageMaker_Clarify
gptkb:Amazon_SageMaker_Pipelines
|
|
gptkbp:bfsLayer
|
8
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
SageMaker Python SDK
|