Azure Data Scientist Associate: Machine Learning Regression Models

Azure    |    Intermediate
  • 10 videos | 1h 12m 7s
  • Includes Assessment
  • Earns a Badge
Rating 4.1 of 7 users Rating 4.1 of 7 users (7)
Machine learning regression models are used to predict numeric labels for the features of an item. In this course, you'll learn more about using regression models in the Azure Machine Learning Studio. First, you'll learn about why regression models are used, the available types of regression models in machine learning, and the steps required to train a regression model. Next, you'll examine the best metrics for determining which regression model to use. You'll learn how to use a subset of data to train the regression model and run the training pipeline. Finally, you'll explore how to use an existing pipeline to create a new inference pipeline and create and deploy a predictive service. This course is one in a collection that prepares learners for the Designing and Implementing a Data Science Solution on Azure (DP-100) exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Describe what regression models are, why they are used, and the available types of regression models in azure machine learning studio
    Describe the steps required to train a regression model
    Describe the best metrics for determining which regression model to use
    Use the azure machine learning designer to train a regression model
  • Use a subset of data to train the regression model and run the training pipeline
    Evaluate a regression model by using an evaluate model in azure machine learning studio
    Use an existing pipeline to create a new inference pipeline to create a predictive service for a regression model
    Deploy a regression model-based inference pipeline that can be used by clients
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 34s
    In this video, you’ll learn more about your instructor and this course. In this course, you’ll learn about regression models in Azure's Machine Learning Studio or ML Studio. You’ll see why regression models are used and the available types of regression models in machine learning. You’ll learn the steps required to train a regression model. You’ll also look at the best metrics for determining which regression model to use. You’ll also create an inference pipeline. FREE ACCESS
  • 7m 28s
    Here, you’ll learn about regression. Regression machine learning is a style of supervised machine learning. This means you can train the model with data that already has the answer. Regression models allow you to predict values based on the features of your data. Once you've trained the model, you can predict labels for new datasets where you don't know the answer. In Azure, you can use machine learning tools to create regression models. FREE ACCESS
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    3.  Regression Model Training Concepts
    7m 31s
    Here, you’ll learn regression model training concepts. First, you’ll need to create a pipeline. A pipeline is where all the steps are defined, configured, and operated against. A pipeline is a recipe for your model. A model is only as good as the data set it uses. You need a reference to your training data. Once you have your data where it needs to be and configured your model training, you can execute your pipeline. FREE ACCESS
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    4.  Regression Model Selection
    6m 1s
    Here, you’ll learn about regression model selection. The data you use to train a model must be meaningful. If you give your model too many features, you’ll have a model that lacks precision. You also don’t want any bias. The model must be as accurate as possible. There are a certain set of metrics provided by Microsoft that help you evaluate your regression model outputs. One of the most common metrics is the R-Squared metric. FREE ACCESS
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    5.  Training a Regression Model
    12m 14s
    Here, you’ll watch a demo. You’ll learn how to create a pipeline in Azure ML Studio to prepare a dataset to be used in a regression pipeline. You’ll create a new pipeline through the designer and then add and configure certain modules to bring a dataset inside. You’ll then cleanse its contents. You'll know it's working if you can execute the pipeline and inspect the data. FREE ACCESS
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    6.  Executing the Regression Model Pipeline
    9m 1s
    Here, you’ll watch a demo. You’ll learn how to build an executor regression model training pipeline. The purpose of this model is to try to predict the price of a car based on its various characteristics. First, you’ll need to open the Azure ML Studio in your browser. You’ll open the pipeline you’ve already created. FREE ACCESS
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    7.  Evaluating a Regression Model
    6m 24s
    Here, you’ll watch a demo. You’ll learn how to add an evaluation module to a regression pipeline in Azure ML Studio. This will allow you to evaluate the results of the candidate model. You’ll learn how to add and configure the module in the pipeline canvas. Finally, you'll execute the pipeline and explore the results of the valuation module. FREE ACCESS
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    8.  Creating an Inference Pipeline
    11m 53s
    Here, you’ll watch a demo. You’ll learn how to create an Inference Pipeline in Azure ML Studio. To do that, you’ll navigate to the Azure ML Studio in your browser. This demo will use what you’ve created in the previous demo. You’ll click on the Designer option in the left-hand option menu. Then, you’ll select your pipeline from the list at the bottom of the page. FREE ACCESS
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    9.  Deploying Regression Model Predictive Services
    9m 13s
    Here, you’ll watch a demo. You’ll learn how to deploy a predictive service using Azure ML Studio. To do that, you’ll piggyback off your last few demos. You’ll use a built-in deployment mechanism against your existing inference pipeline to create a new endpoint. You'll know your deployment is working if you can access the results externally using Postman. First, you’ll need to navigate to the Azure ML Studio in your browser. FREE ACCESS
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    10.  Course Summary
    47s
    In this video, you’ll summarize what you’ve learned in this course. You’ve examined machine learning regression models in Azure. You explored what regression models are, why they're used, and which ones are available in Azure. You learned how to train and select a regression model. You ran the regression model training pipeline. You also learned the regression model evaluation in Azure Machine Learning Studio. FREE ACCESS

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