Cloud Data Science: Optimize and Validate Models in Azure Machine Learning Studio


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level


Overview/Description

Discover how to optimize and validate models in Azure Machine Learning Studio.



Expected Duration (hours)
1.1

Lesson Objectives

Cloud Data Science: Optimize and Validate Models in Azure Machine Learning Studio

  • use the Split Data module to divide your dataset in Azure Machine Learning Studio
  • use the Partition and Sample module to sample or partition your dataset in Azure Machine Learning Studio
  • use the stacking method to build an ensemble in Azure Machine Learning Studio
  • identify the four steps to optimize parameters in Azure Machine Learning Studio
  • describe hyperparameters and the two types of methods used in Azure Machine Learning Studio
  • use the Tune Model Hyperparameters module to perform a parameter sweep in Azure Machine Learning Studio
  • use the Evaluate Model module to evaluate a trained model in Azure Machine Learning Studio
  • use the Cross Validate Model module to divide your data into partitions in Azure Machine Learning Studio
  • use the Evaluate Recommender module to measure accuracy of predictions in Azure Machine Learning Studio
  • describe the metrics for classification models in Azure Machine Learning Studio
  • describe the metrics for regression models in Azure Machine Learning Studio
  • describe the metrics for clustering models in Azure Machine Learning Studio
  • optimize and validate models in Azure Machine Learning Studio

    • Course Number:
    it_dfpdsm_09_enus

    Expertise Level
    Expert