Getting Started with Azure Machine Learning Studio

By Kevin Hu

Jumpstart your organization’s machine learning initiative using the simple Azure Machine Learning interface!

2 hours
  • 23 Lessons

About the course

With artificial intelligence and machine learning becoming ubiquitous, any organization can access these technologies easily. As AI/ML becomes widely adopted, expertise on Azure Machine Learning will be high in demand. Gone are the days when you would need an advanced degree to practice machine learning!

This course introduces terminology used in machine learning, along with all of the steps in the process from start to finish. We’ll also learn how to work within the Azure Machine Learning studio to create a simple machine learning model. After completing the course, you’ll be able to:

  • talk about the relevance of machine learning in today’s technological landscape
  • understand the basic concepts, terms, and steps of the machine learning process
  • build a simple machine learning model in the Azure Machine Learning studio.

No prior coding experience is required, and while it helps to have some familiarity with Azure, the course material will be a fit for anyone who is interested in machine learning but not sure how to get started.

  • Chapter 1 7 Lessons Machine Learning Concepts 26:40

    An Important Note About A Cloud Guru and Linux Academy Courses

    1:18

    An Overview of Machine Learning Concepts

    2:11

    Introduction to Azure Platform

    4:18

    Working with Data

    5:46

    Supervised Machine Learning

    5:23

    Unsupervised Machine Learning

    4:25

    Summary

    3:19
  • Chapter 2 3 Lessons Azure Machine Learning 14:13

    What is Azure Machine Learning?

    1:14

    Lab (Part 1): Create Azure Machine Learning Workspace

    8:26

    Azure Machine Learning Pricing

    4:33
  • Chapter 3 9 Lessons Machine Learning Workflow 1:04:04

    Introduction

    1:02

    The Steps

    2:08

    Getting Data

    2:13

    Lab (Part 2): Add, Explore and Understand Data

    8:03

    Lab (Part 3): Wrangle Data

    14:28

    Lab (Part 4): Finish Your Azure ML Experiment

    12:40

    What is Data Wrangling?

    5:27

    Train , Test, Evaluate

    15:11

    Summary

    2:52
  • Chapter 4 3 Lessons Constant Improvement 23:03

    Machine Learning is an Iterative Process

    2:23

    Lab (Part 5): Continue to Improve the Model

    18:41

    Summary

    1:59
  • Chapter 5 1 Lesson Wrapping Up 3:13

    Conclusion

    3:13

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