Class

MLUpdateTask

A task that updates a model with additional training data.

Declaration

class MLUpdateTask : MLTask

Overview

Use an MLUpdateTask to update a machine learning model on a user’s device.

Topics

Creating an Update Task

init(forModelAt: URL, trainingData: MLBatchProvider, configuration: MLModelConfiguration?, completionHandler: (MLUpdateContext) -> Void)

Creates an update task for your model, given its file URL, training data, and your completion handler.

init(forModelAt: URL, trainingData: MLBatchProvider, configuration: MLModelConfiguration?, progressHandlers: MLUpdateProgressHandlers)

Creates an update task for your model, given its file URL, training data, and your progress handlers.

protocol MLBatchProvider

An interface that represents a collection of feature providers.

class MLModelConfiguration

The settings for creating or updating a machine learning model.

class MLUpdateContext

The context an update task provides to your app’s completion and update progress handlers.

class MLUpdateProgressHandlers

A collection of closures an update task uses to notify your app of its progress.

Starting and Resuming an Update

func resume(withParameters: [MLParameterKey : Any])

Resumes a model update with updated parameter values.

class MLParameterKey

A key for model and update parameter dictionaries.

Supporting Types

class MLTask

An abstract base class for machine learning tasks.

Relationships

Inherits From

Conforms To

See Also

Model Updates

Personalizing a Model with On-Device Updates

Modify an updatable Core ML model by running an update task with labeled data.