SKILL BENCHMARK

Predictive Analytics in Operations Competency (Intermediate Level)

  • 18m
  • 18 questions
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The Predictive Analytics in Operations Competency (Intermediate Level) benchmark measures your ability to apply suitable machine learning algorithms and perform predictive analytics for various use cases in the operations field. You will be evaluated on your skills in viewing important model attributes, comparing and evaluating model performance, and optimizing the models. A learner who scores high on this benchmark demonstrates that they have experience in performing predictive analytics and performance tuning of models in operations.

Topics covered

  • analyze a machine failure prediction dataset
  • compare the performance of the logistic regression and decision forest models
  • create an Azure Machine Learning workspace and upload a file as a dataset
  • create and configure a decision forest model for machine failure prediction
  • create a pipeline for a machine failure prediction model
  • observe model explanations and performance metrics for machine failure prediction models
  • perform hyperparameter tuning on a machine failure prediction model and view the results
  • perform preparations on machine failure prediction data
  • predict machine failure using decision forests and compare the performance to the logistic regression model
  • set up a machine learning (ML) model for machine failure prediction
  • standardize data using a component
  • use pipelines to prepare machine failure data
  • use SMOTE to improve the performance of a machine failure prediction model
  • view important machine failure prediction attributes
  • view the dataset profile and create a pipeline
  • view the effects of standardizing machine failure data
  • view the performance of a machine failure prediction model
  • visualize data for machine failure prediction