Azure AI Fundamentals: Evaluating Models in Azure AI

Azure 2024    |    Beginner
  • 16 videos | 1h 35m 34s
  • Includes Assessment
  • Earns a Badge
Rating 4.0 of 1 users Rating 4.0 of 1 users (1)
In order to build a useful machine learning deployment, you must be able to evaluate and verify the AI model and data, as well as the accuracy and effectiveness of its predictions. Azure Machine Learning Studio and the designer provide multiple easy-to-use methods for evaluating and scoring a model. In this course, you will learn how to score and evaluate models, how to run pipelines, and how to analyze evaluation output. Then you will dig into evaluation results, visualizing data in a scoring model, assessing regression model results, and investigating classification model results. Finally, you will explore clustering model results, inference pipelines, web service output, and predictive service deployment. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Add a scoring model component in azure machine language designer
    Describe various model evaluation types, such as mean absolute error (mae) and r2
    Use an evaluator on a model and interpret the metrics
    Run and monitor a complete pipeline
    Analyze evaluation results in the output and logs section in azure machine language designer
    Identify and investigate details of evaluation results
    Visualize scoring data from a scoring model
  • Investigate logs and results after running a regression model
    Interpret logs and results after running a classification model
    Interpret the logs and results after running a clustering model
    Create an inference pipeline using a python script
    Add a web service output to provide external access to a model
    Deploy a model as a predictive service
    Test a predictive service from an external app
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 2s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 6m 18s
    In this video, find out how to add a scoring model component in Azure Machine Language designer. FREE ACCESS
  • Locked
    3.  Exploring Model Evaluation Types
    7m 8s
    After completing this video, you will be able to describe various model evaluation types, such as Mean Absolute Error (MAE) and R2. FREE ACCESS
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    4.  Using Evaluators
    7m 2s
    Learn how to use an evaluator on a model and interpret the metrics. FREE ACCESS
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    5.  Running Pipelines
    5m 55s
    During this video, discover how to run and monitor a complete pipeline. FREE ACCESS
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    6.  Analyzing Evaluation Output
    6m 43s
    In this video, you will learn how to analyze evaluation results in the output and logs section in Azure Machine Language Designer. FREE ACCESS
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    7.  Exploring Evaluation Results
    7m 51s
    Find out how to identify and investigate details of evaluation results. FREE ACCESS
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    8.  Visualizing Data in a Scoring Model
    7m 4s
    Discover how to visualize scoring data from a scoring model. FREE ACCESS
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    9.  Assessing Regression Model Results
    7m 5s
    During this video, you will learn how to investigate logs and results after running a regression model. FREE ACCESS
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    10.  Investigating Classification Model Results
    7m 7s
    In this video, find out how to interpret logs and results after running a classification model. FREE ACCESS
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    11.  Interpreting Clustering Model Results
    7m 40s
    During this video, discover how to interpret the logs and results after running a clustering model. FREE ACCESS
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    12.  Creating an Inference Pipeline
    5m 39s
    Learn how to create an inference pipeline using a Python script. FREE ACCESS
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    13.  Adding a Web Service Output
    5m 50s
    In this video, find out how to add a web service output to provide external access to a model. FREE ACCESS
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    14.  Deploying Predictive Services
    6m 5s
    Discover how to deploy a model as a predictive service. FREE ACCESS
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    15.  Testing Predictive Services
    6m 20s
    Find out how to test a predictive service from an external app. FREE ACCESS
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    16.  Course Summary
    47s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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