Data science and machine learning professionals work tirelessly to improve the quality of their ML models. In this course, Evaluating Model Effectiveness in Microsoft Azure, you will learn how to use Azure Machine Learning Studio to improve your models. First, you will learn how to evaluate model effectiveness in Azure. Next, you will discover how to improve model performance by eliminating overfitting and implementing ensembling. Finally, you will explore how to assess ML model interpretability. When you are finished with this course, you will have the skills and knowledge of Azure Machine Learning needed to ensure your ML models are consistent, accurate, and explainable.
Course Overview [Autogenerated] Hi, everyone. My name is Tim Warner. Welcome to my course. Evaluating Model Effectiveness and Microsoft Asher. I'm a plural site. Staff author. Microsoft M V. P and Microsoft Asher Solution Architect This intermediate level courses for data science practitioners who work with There's Your Machine Learning Service and who seek to improve their ML model effectiveness. By the end of the course, you'll understand how to use as your machine learning tools to evaluate model effectiveness, improved model performance and assess model. Explain ability. I hope you'll join me on this journey to master the Ascher Machine Learning Model development process and are evaluating model Effectiveness and Microsoft Azure Course plural site.