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Pluralsight

Training Models with Amazon SageMaker

via Pluralsight

Overview

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In today’s fast-paced world of machine learning, knowing how to efficiently train and deploy models is crucial for any data professional. In this course, Training Models with Amazon SageMaker, you'll learn to develop key skills for managing machine learning workflows on AWS. First, you’ll learn to train models using Amazon SageMaker’s built-in algorithms, custom frameworks, and hyperparameter tuning capabilities. Then, you’ll explore how to use SageMaker’s built-in algorithms to quickly set up and run model training jobs. Next, you’ll discover how to implement custom algorithms and frameworks like PyTorch and TensorFlow for more tailored machine learning solutions. Finally, you’ll learn how to perform hyperparameter tuning to optimize your model performance with minimal manual effort. When you’re finished with this course, you’ll have the skills and knowledge of training machine learning models on Amazon SageMaker, equipping you to streamline your machine learning workflows and enhance model performance in real-world scenarios.

Syllabus

  • Training Models with Amazon SageMaker 17mins

Taught by

Jacob Lyman (Jake)

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