In order to build a powerful and 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'll learn how to score and evaluate models and interpret and evaluate the results from some common models. You'll also explore how to create an inference pipeline, add web service output to provide external access to the model, and deploy and test a predictive web service. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.
Learning Objectives
{"discover the key concepts covered in this course"}