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
Overview
Syllabus
- Course Introduction
- Azure Machine Learning Pipelines
- Machine Learning Algorithm
- Feature Selection
- Classic Machine Learning Models
- Run Training Scripts in an Azure Machine Learning Workspace
- Generate Metrics from an Experiment Run
- Conclusion
Taught by
Brian Roehm