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]

# Install 'sagemaker.mlframework' in R:

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

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

On CRAN:

amazon-sagemaker aws machine-learning sagemaker sdk

2.48 score 2 packages 69 exports 43 dependencies

Last updated 3 years agofrom:e1988da8e0. Checks:OK: 1 ERROR: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Oct 29 2024
R-4.5-win	ERROR	Oct 29 2024
R-4.5-linux	ERROR	Oct 29 2024
R-4.4-win	ERROR	Oct 29 2024
R-4.4-mac	ERROR	Oct 29 2024
R-4.3-win	ERROR	Oct 29 2024
R-4.3-mac	ERROR	Oct 29 2024

Exports:.SparkProcessorBase AutoML AutoMLInput AutoMLJob CandidateEstimator CandidateStep Chainer ChainerModel ChainerPredictor FactorizationMachines FactorizationMachinesModel FactorizationMachinesPredictor HuggingFace HuggingFaceModel HuggingFacePredictor HuggingFaceProcessor IPInsights IPInsightsModel IPInsightsPredictor KMeans KMeansModel KMeansPredictor KNN KNNModel KNNPredictor LDA LDAModel LDAPredictor LinearLearner LinearLearnerModel LinearLearnerPredictor MXNet MXNetModel MXNetPredictor MXNetProcessor NTM NTMModel NTMPredictor Object2Vec Object2VecModel PCA PCAModel PCAPredictor PySparkProcessor PyTorch PyTorchModel PyTorchPredictor PyTorchProcessor RandomCutForest RandomCutForestModel RandomCutForestPredictor RLEstimator RLFramework RLToolkit SKLearn SKLearnModel SKLearnPredictor SKLearnProcessor SparkJarProcessor SparkMLModel SparkMLPredictor TensorFlow TensorFlowModel TensorFlowPredictor TensorFlowProcessor XGBoost XGBoostModel XGBoostPredictor XGBoostProcessor

Dependencies:askpass base64enc cli curl data.table digest fs httr jsonlite lgr listenv mime openssl paws paws.analytics paws.application.integration paws.common paws.compute paws.cost.management paws.customer.engagement paws.database paws.developer.tools paws.end.user.computing paws.machine.learning paws.management paws.networking paws.security.identity paws.storage processx ps R6 Rcpp rlang sagemaker.common sagemaker.core sagemaker.debugger sagemaker.mlcore sys triebeard urltools uuid xml2 zip

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
r6 sagemaker: this is just a placeholder	sagemaker.mlframework-package sagemaker.mlframework
Handles Amazon SageMaker processing tasks for jobs using Spark.	.SparkProcessorBase
AutoML Class	AutoML
Accepts parameters that specify an S3 input for an auto ml job	AutoMLInput
AutoMLJob class	AutoMLJob
CandidateEstimator Class	CandidateEstimator
CandidateStep Class	CandidateStep
Chainer Class	Chainer
ChainerModel Class	ChainerModel
A Predictor for inference against Chainer Endpoints.	ChainerPredictor
A supervised learning algorithm used in classification and regression.	FactorizationMachines
Amazon FactorizationMachinesModel Class	FactorizationMachinesModel
Performs binary-classification or regression prediction from input vectors.	FactorizationMachinesPredictor
HuggingFace estimator class	HuggingFace
HuggingFaceModel Class	HuggingFaceModel
A Predictor for inference against Hugging Face Endpoints.	HuggingFacePredictor
HuggingFaceProcessor class	HuggingFaceProcessor
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 Class	MXNet
MXNetModel Class	MXNetModel
MXNetPredictor Class	MXNetPredictor
MXNetProcessor class	MXNetProcessor
An unsupervised learning algorithm used to organize a corpus of documents into topics	NTM
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 Class	PySparkProcessor
PyTorch Class	PyTorch
PyTorchModel class	PyTorchModel
A Predictor for inference against PyTorch Endpoints.	PyTorchPredictor
PyTorchProcessor class	PyTorchProcessor
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 Class	RLEstimator
RLFramework enum environment list	RLFramework
RLToolkit enum environment list	RLToolkit
Scikit-learn Class	SKLearn
SKLearnModel Class	SKLearnModel
A Predictor for inference against Scikit-learn Endpoints.	SKLearnPredictor
SKLearnProcessor Class	SKLearnProcessor
SparkJarProcessor Class	SparkJarProcessor
SparkMLModel class	SparkMLModel
Performs predictions against an MLeap serialized SparkML model.	SparkMLPredictor
TensorFlow Class	TensorFlow
TensorFlowModel Class	TensorFlowModel
TensorFlowPredictor Class	TensorFlowPredictor
TensorFlowProcessor Class	TensorFlowProcessor
XGBoost Class	XGBoost
XGBoostModel Class	XGBoostModel
XGBoostPredictor Class	XGBoostPredictor
XGBoostProcessor class	XGBoostProcessor