Package: sagemaker.mlframework 0.2.0

sagemaker.mlframework: sagemaker machine learning developed by amazon

`sagemaker` machine learning developed by amazon.

Authors:Dyfan Jones [aut, cre], Amazon.com, Inc. [cph]

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sagemaker.mlframework.pdf |sagemaker.mlframework.html
sagemaker.mlframework/json (API)
NEWS

# Install sagemaker.mlframework in R:
install.packages('sagemaker.mlframework', repos = c('https://dyfanjones.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/dyfanjones/sagemaker-r-mlframework/issues

On CRAN:

amazon-sagemakerawsmachine-learningsagemakersdk

69 exports 0.71 score 43 dependencies 2 dependents

Last updated 2 years agofrom:e1988da8e0767e790b484229556dc8bbcde5017a

Exports:.SparkProcessorBaseAutoMLAutoMLInputAutoMLJobCandidateEstimatorCandidateStepChainerChainerModelChainerPredictorFactorizationMachinesFactorizationMachinesModelFactorizationMachinesPredictorHuggingFaceHuggingFaceModelHuggingFacePredictorHuggingFaceProcessorIPInsightsIPInsightsModelIPInsightsPredictorKMeansKMeansModelKMeansPredictorKNNKNNModelKNNPredictorLDALDAModelLDAPredictorLinearLearnerLinearLearnerModelLinearLearnerPredictorMXNetMXNetModelMXNetPredictorMXNetProcessorNTMNTMModelNTMPredictorObject2VecObject2VecModelPCAPCAModelPCAPredictorPySparkProcessorPyTorchPyTorchModelPyTorchPredictorPyTorchProcessorRandomCutForestRandomCutForestModelRandomCutForestPredictorRLEstimatorRLFrameworkRLToolkitSKLearnSKLearnModelSKLearnPredictorSKLearnProcessorSparkJarProcessorSparkMLModelSparkMLPredictorTensorFlowTensorFlowModelTensorFlowPredictorTensorFlowProcessorXGBoostXGBoostModelXGBoostPredictorXGBoostProcessor

Dependencies:askpassbase64encclicurldata.tabledigestfshttrjsonlitelgrlistenvmimeopensslpawspaws.analyticspaws.application.integrationpaws.commonpaws.computepaws.cost.managementpaws.customer.engagementpaws.databasepaws.developer.toolspaws.end.user.computingpaws.machine.learningpaws.managementpaws.networkingpaws.security.identitypaws.storageprocessxpsR6Rcpprlangsagemaker.commonsagemaker.coresagemaker.debuggersagemaker.mlcoresystriebeardurltoolsuuidxml2zip

Readme and manuals

Help Manual

Help pageTopics
r6 sagemaker: this is just a placeholdersagemaker.mlframework-package sagemaker.mlframework
Handles Amazon SageMaker processing tasks for jobs using Spark..SparkProcessorBase
AutoML ClassAutoML
Accepts parameters that specify an S3 input for an auto ml jobAutoMLInput
AutoMLJob classAutoMLJob
CandidateEstimator ClassCandidateEstimator
CandidateStep ClassCandidateStep
Chainer ClassChainer
ChainerModel ClassChainerModel
A Predictor for inference against Chainer Endpoints.ChainerPredictor
A supervised learning algorithm used in classification and regression.FactorizationMachines
Amazon FactorizationMachinesModel ClassFactorizationMachinesModel
Performs binary-classification or regression prediction from input vectors.FactorizationMachinesPredictor
HuggingFace estimator classHuggingFace
HuggingFaceModel ClassHuggingFaceModel
A Predictor for inference against Hugging Face Endpoints.HuggingFacePredictor
HuggingFaceProcessor classHuggingFaceProcessor
An unsupervised learning algorithm that learns the usage patterns for IPv4 addresses.IPInsights
Reference IPInsights s3 model data.IPInsightsModel
Returns dot product of entity and IP address embeddings as a score for compatibility.IPInsightsPredictor
An unsupervised learning algorithm that attempts to find discrete groupings within data.KMeans
Reference KMeans s3 model data.KMeansModel
Assigns input vectors to their closest cluster in a KMeans model.KMeansPredictor
An index-based algorithm. It uses a non-parametric method for classification or regression.KNN
Reference S3 model data created by KNN estimator.KNNModel
Performs classification or regression prediction from input vectors.KNNPredictor
An unsupervised learning algorithm attempting to describe data as distinct categories.LDA
Reference LDA s3 model data created by LDA estimator.LDAModel
Transforms input vectors to lower-dimesional representations.LDAPredictor
A supervised learning algorithms used for solving classification or regression problems.LinearLearner
Reference LinearLearner s3 model data.LinearLearnerModel
Performs binary-classification or regression prediction from input vectors.LinearLearnerPredictor
MXNet ClassMXNet
MXNetModel ClassMXNetModel
MXNetPredictor ClassMXNetPredictor
MXNetProcessor classMXNetProcessor
An unsupervised learning algorithm used to organize a corpus of documents into topicsNTM
Reference NTM s3 model data.NTMModel
Transforms input vectors to lower-dimesional representations.NTMPredictor
A general-purpose neural embedding algorithm that is highly customizable.Object2Vec
Reference Object2Vec s3 model data.Object2VecModel
An unsupervised machine learning algorithm to reduce feature dimensionality.PCA
Reference PCA s3 model data.PCAModel
Transforms input vectors to lower-dimesional representations.PCAPredictor
PySparkProcessor ClassPySparkProcessor
PyTorch ClassPyTorch
PyTorchModel classPyTorchModel
A Predictor for inference against PyTorch Endpoints.PyTorchPredictor
PyTorchProcessor classPyTorchProcessor
An unsupervised algorithm for detecting anomalous data points within a data set.RandomCutForest
Reference RandomCutForest s3 model data.RandomCutForestModel
Assigns an anomaly score to each of the datapoints provided.RandomCutForestPredictor
RLEstimator ClassRLEstimator
RLFramework enum environment listRLFramework
RLToolkit enum environment listRLToolkit
Scikit-learn ClassSKLearn
SKLearnModel ClassSKLearnModel
A Predictor for inference against Scikit-learn Endpoints.SKLearnPredictor
SKLearnProcessor ClassSKLearnProcessor
SparkJarProcessor ClassSparkJarProcessor
SparkMLModel classSparkMLModel
Performs predictions against an MLeap serialized SparkML model.SparkMLPredictor
TensorFlow ClassTensorFlow
TensorFlowModel ClassTensorFlowModel
TensorFlowPredictor ClassTensorFlowPredictor
TensorFlowProcessor ClassTensorFlowProcessor
XGBoost ClassXGBoost
XGBoostModel ClassXGBoostModel
XGBoostPredictor ClassXGBoostPredictor
XGBoostProcessor classXGBoostProcessor