Azure AI Fundamentals: Evaluating Models in Azure AI

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. In order to build a useful machine learning deployment, you must be able to evaluate and verify the AI model and data, as well as the accuracy and effectiveness of its predictions. Azure Machine Learning Studio and the designer provide multiple easy-to-use methods for evaluating and scoring a model. In this course, you will learn how to score and evaluate models, how to run pipelines, and how to analyze evaluation output. Then you will dig into evaluation results, visualizing data in a scoring model, assessing regression model results, and investigating classification model results. Finally, you will explore clustering model results, inference pipelines, web service output, and predictive service deployment. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.