Hyperparameter tuning and optimization of your ML model are essential parts of the model development process to generate the most accurate predictions. Amazon SageMaker gives you everything you need to cost-effectively train and tune ML models at scale without having 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 goals:
* Objective 1: Learn how hyperparameter works, including setting metrics and ranges.
* Objective 2: Discover 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 covered in this talk, visit: https://aws.amazon.com/sagemaker/train/
****To download a copy of the slide deck from this webinar, visit: https://pages.awscloud.com/Maximize-accuracy-of-your-ML-model-with-advanced-hyperparameter-tuning- strategies_2022_1017-MCL_OD Subscribe to AWS Online Tech Talks on AWS:
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