AWS Certified Machine Learning - Specialty (MLS-C01): Modeling

What you'll learn

This course is part of a series, designed to help you prepare for the AWS Certified Machine Learning - Specialty (MLS-C01) exam. The courses in this series are focused on the domains from the exam guide, and we recommend taking them in this order: * AWS Certified Machine Learning - Specialty (MLS-C01): Data Engineering * AWS Certified Machine Learning - Specialty (MLS-C01): Exploratory Data Analysis * AWS Certified Machine Learning - Specialty (MLS-C01): Modeling * AWS Certified Machine Learning - Specialty (MLS-C01): Machine Learning Implementation and Operations * AWS Certified Machine Learning - Specialty (MLS-C01): Exam Preparation In this course, AWS Certified Machine Learning - Specialty (MLS-C01): Modeling, you’ll learn to select the right algorithms to solve a business problem, train, and evaluate an ML model for optimal performance. First, you’ll explore how to determine when, and when not, to use machine learning. Next, you’ll discover the various built-in algorithms provided by Amazon Sagemaker. Then, you'll understand how to train an ML model using various Amazon SageMaker features. Finally, you’ll learn how to optimally tune hyper-parameters and evaluate the model using the various metrics. When you’re finished with this course, you’ll have the skills and knowledge to effectively build, train, and evaluate an ML model needed to develop a high-quality machine-learning model that produces accurate predictions.