Amazon SageMaker provides broad-set capabilities for machine learning (ML) as it helps to prepare, train, and quickly deploy ML models. Use this course to learn more about the basic capabilities of SageMaker and work with it to implement solutions to various machine learning problems.
Explore features and functionalities of SageMaker through practical demos and discover how to implement hyperparameter tuning. This course will also help you explore algorithms in SageMaker, such as linear learner, XGBoost, object detection, and semantic segmentation.
After completing this course, you'll be able to train and tune a range of algorithms in order to solve simple classification tasks for natural language processing (NLP) and computer vision.
Learning Objectives
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