Deploying Models with Azure Machine Learning
This course will teach you how to navigate the Azure ML platform, create a workspace, find and fine-tune models, deploy it, and perform high-level fairness and interpretability assessments.
What you'll learn
Navigating the world of machine learning can be challenging, especially for beginners. In this course, Deploying Models with Azure Machine Learning, you’ll learn to effectively utilize the Azure ML platform to build, deploy, and assess machine learning models. First, you’ll explore the core components of Azure ML, including workspaces, compute resources, and data stores. Next, you’ll discover how to find and fine-tune models using the model catalog and conduct experiments with custom datasets. Finally, you’ll learn how to deploy these models and perform high-level fairness and interpretability assessments to ensure ethical AI practices. When you’re finished with this course, you’ll have the skills and knowledge of Azure Machine Learning needed to confidently build, deploy, and assess machine learning models on the Azure platform.
Table of contents
About the author
Axel Sirota is a Microsoft Certified Trainer with a deep interest in Deep Learning and Machine Learning Operations. He has a Masters degree in Mathematics and after researching in Probability, Statistics and Machine Learning optimisation, he works as an AI and Cloud Consultant as well as being an Author and Instructor at Pluralsight, Develop Intelligence, and O'Reilly Media.