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MachineLearning module#

Index > MachineLearning

Auto-generated documentation for MachineLearning type annotations stubs module types-boto3-machinelearning.

How to install#

You can generate type annotations for boto3 package locally with mypy_boto3_builder. Use uv for build isolation.

  1. Run mypy-boto3-builder in your package root directory: uvx --with 'boto3==1.35.86' mypy_boto3_builder
  2. Select boto3 AWS SDK.
  3. Add MachineLearning service.
  4. Use provided commands to install generated packages.

VSCode extension#

Add AWS Boto3 extension to your VSCode and run AWS boto3: Quick Start command.

Click Modify and select boto3 common and MachineLearning.

From PyPI with pip#

Install types-boto3 for MachineLearning service.

# install with boto3 type annotations
python -m pip install 'types-boto3[machinelearning]'

# Lite version does not provide session.client/resource overloads
# it is more RAM-friendly, but requires explicit type annotations
python -m pip install 'types-boto3-lite[machinelearning]'

# standalone installation
python -m pip install types-boto3-machinelearning

How to uninstall#

python -m pip uninstall -y types-boto3-machinelearning

Usage#

Code samples can be found in Examples.

MachineLearningClient#

Type annotations and code completion for boto3.client("machinelearning") as MachineLearningClient boto3 documentation

# MachineLearningClient usage example

from boto3.session import Session

from types_boto3_machinelearning.client import MachineLearningClient

def get_client() -> MachineLearningClient:
    return Session().client("machinelearning")

Paginators#

Type annotations and code completion for paginators from boto3.client("machinelearning").get_paginator("...").

# DescribeBatchPredictionsPaginator usage example

from boto3.session import Session

from types_boto3_machinelearning.paginator import DescribeBatchPredictionsPaginator

def get_describe_batch_predictions_paginator() -> DescribeBatchPredictionsPaginator:
    return Session().client("machinelearning").get_paginator("describe_batch_predictions"))

Waiters#

Type annotations and code completion for waiters from boto3.client("machinelearning").get_waiter("...").

# BatchPredictionAvailableWaiter usage example

from boto3.session import Session

from types_boto3_machinelearning.waiter import BatchPredictionAvailableWaiter

def get_batch_prediction_available_waiter() -> BatchPredictionAvailableWaiter:
    return Session().client("machinelearning").get_waiter("batch_prediction_available")

Literals#

Type annotations for literals used in methods and schema.

# AlgorithmType usage example

from types_boto3_machinelearning.literals import AlgorithmType

def get_value() -> AlgorithmType:
    return "sgd"

Type definitions#

Type annotations for type definitions used in methods and schema.