Maximize accuracy of your ML model with advanced hyperparameter tuning strategies

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Published Feb 20, 2025

Hyperparameter tuning and optimization of your ML model are essential parts of the model development process to generate the most accurate predictions. Amazon SageMaker provides you with everything you need to train and tune ML models cost effectively at scale without the need to manage infrastructure. Join this session to learn how to efficiently tune your ML models and improve accuracy using the latest techniques by running a large-scale Amazon SageMaker Automatic Model Tuning job.

Learning Objectives:
* Objective 1: Learn how hyperparameter works including setting up metrics and ranges.
* Objective 2: Explore how to manage and scale your hyperparameter tuning jobs.
* Objective 3: Deep dive into best practices for hyperparameter tuning.

***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/sagemaker/train/
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