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* <p>Creates an Autopilot job also referred to as Autopilot experiment or AutoML job.</p>
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* <p>An AutoML job in SageMaker is a fully automated process that allows you to build machine
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* learning models with minimal effort and machine learning expertise. When initiating an
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* AutoML job, you provide your data and optionally specify parameters tailored to your use
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* case. SageMaker then automates the entire model development lifecycle, including data
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* preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify
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* and accelerate the model building process by automating various tasks and exploring
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* different combinations of machine learning algorithms, data preprocessing techniques, and
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* hyperparameter values. The output of an AutoML job comprises one or more trained models
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* ready for deployment and inference. Additionally, SageMaker AutoML jobs generate a candidate
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* model leaderboard, allowing you to select the best-performing model for deployment.</p>
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* <p>For more information about AutoML jobs, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html">https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html</a>
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* in the SageMaker developer guide.</p>
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* <note>
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* <p>We recommend using the new versions <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a> and <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJobV2.html">DescribeAutoMLJobV2</a>, which offer backward compatibility.</p>
* <p>Creates an Autopilot job also referred to as Autopilot experiment or AutoML job V2.</p>
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* <p>An AutoML job in SageMaker is a fully automated process that allows you to build machine
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* learning models with minimal effort and machine learning expertise. When initiating an
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* AutoML job, you provide your data and optionally specify parameters tailored to your use
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* case. SageMaker then automates the entire model development lifecycle, including data
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* preprocessing, model training, tuning, and evaluation. AutoML jobs are designed to simplify
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+
* and accelerate the model building process by automating various tasks and exploring
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* different combinations of machine learning algorithms, data preprocessing techniques, and
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* hyperparameter values. The output of an AutoML job comprises one or more trained models
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* ready for deployment and inference. Additionally, SageMaker AutoML jobs generate a candidate
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* model leaderboard, allowing you to select the best-performing model for deployment.</p>
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* <p>For more information about AutoML jobs, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html">https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html</a>
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* in the SageMaker developer guide.</p>
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* <p>AutoML jobs V2 support various problem types such as regression, binary, and multiclass
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* classification with tabular data, text and image classification, time-series forecasting,
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* and fine-tuning of large language models (LLMs) for text generation.</p>
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* <note>
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* <p>
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* <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html">CreateAutoMLJobV2</a> and <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeAutoMLJobV2.html">DescribeAutoMLJobV2</a> are new versions of <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJob.html">CreateAutoMLJob</a>
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