<!--
{
  "documentType" : "article",
  "framework" : "MLCompute",
  "identifier" : "/documentation/MLCompute/optimizers",
  "metadataVersion" : "0.1.0",
  "role" : "collectionGroup",
  "title" : "Optimizers"
}
-->

# Optimizers

Create an optimizer to use with the training graph.

## Topics

### Optimizer Types

[`class MLCSGDOptimizer`](/documentation/MLCompute/MLCSGDOptimizer)

An optimizer that represents the stochastic gradient decent algorithm.

[`class MLCRMSPropOptimizer`](/documentation/MLCompute/MLCRMSPropOptimizer)

An optimizer that represents the root mean square propagation algorithm.

[`class MLCAdamOptimizer`](/documentation/MLCompute/MLCAdamOptimizer)

An optimizer that represents the adaptive moment estimation algorithm.

[`class MLCAdamWOptimizer`](/documentation/MLCompute/MLCAdamWOptimizer)

An optimizer that represents the Adam algorithm with weight decay.

[`class MLCOptimizer`](/documentation/MLCompute/MLCOptimizer)

The base class for all framework optimizers.

### Supporting Types

[`class MLCOptimizerDescriptor`](/documentation/MLCompute/MLCOptimizerDescriptor)

A configuration object you use to create an optimizer.

[`enum MLCRegularizationType`](/documentation/MLCompute/MLCRegularizationType)

A regularization function to use with an optimizer.


---

Copyright &copy; 2026 Apple Inc. All rights reserved. | [Terms of Use](https://www.apple.com/legal/internet-services/terms/site.html) | [Privacy Policy](https://www.apple.com/privacy/privacy-policy)