In this course, we focus on how to run experiments and train models in Azure Machine Learning. This course is part two of a three part series, focusing on preparation for the DP-100 exam.
We examine how to:
- Create models using Azure Machine Learning designer
- Run training scripts in an Azure Machine Learning workspace
- Generate metrics from an experiment run
- Build a foundation using key algorithms, features, and machine learning models
- Use important tools such as PyTorch, Scikit-learn, Keras, and Chainer
Table of contents
About the author
Brian Roehm
I am a multi cloud certified architect. I have consulted, trained, and worked with executives and IT professionals to understand, design, and implement cloud-based solutions.
At A Cloud Guru, I created compelling training to teach architects, developers, and IT professionals how to implement cutting edge technology and achieve cloud certifications. At Cerner and Lone Light Analytics, I developed cloud-based solutions in Azure and AWS and consulted with business groups and clients to manage and migrate solutions into the cloud.
In addition, I am a PMP certified project manager and adjunct professor at Mid America Nazarene University. I apply my knowledge of business strategy, project management, agile software development, and IT infrastructure to streamline business function and foster business growth. I have managed all aspects of the SDLC process and created and managed multiple project management offices.
