Course curriculum

    1. Overview

    2. Prerequisites

    3. Project Overview

    4. Identifying a Classification scenario

    5. Classification examples

    6. Navigate to Azure ML

    7. Choose source for Dataset

    8. Review Settings and Schema

    9. Create Data asset

    10. Start Computing Instance

    11. Create new Pipeline

    12. Discuss about workspace

    13. Select Input

    14. Select Columns

    15. Normalize Data

    16. Split Data

    1. Train Model

    2. Score Model

    3. Evaluate Model

    4. Review Results

    5. Analyze Results in detail

    6. ROC curve

    7. Area of Improvements

    8. Create Inference Pipeline

    9. Provide manual inputs

    10. Run Inference Pipeline

    11. Deploy Model

    12. Test new data

    13. Cleanup resources

    14. Summary

    15. Congratulations on completing this course!

About this course

  • $295.00
  • 31 lessons
  • 1 hour of video content