-
Course
- AI
Training Models with Amazon SageMaker
This course will teach you how to leverage built-in algorithms, use custom frameworks, and fine-tune hyperparameters in SageMaker, giving you the skills to streamline your machine learning workflows.
What you'll learn
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.
Table of contents
About the author
I'm a data professional specializing in scaling Al, Machine Learning, and Data Science practices and teams. I make videos and write articles on cutting-edge technologies.
More Courses by Jacob