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Designing Machine Learning Solutions on Microsoft Azure

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David Tucker

1:40:23

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  • 01 - Course Overview.mp4
    01:25
  • 02 - Overview.mp4
    01:11
  • 03 - Data Science Challenges.mp4
    03:19
  • 04 - Introduction to Team Data Science Process.mp4
    05:30
  • 05 - TDSP Data Science Lifecycle.mp4
    06:19
  • 06 - Reviewing TDSP Resources.mp4
    04:21
  • 07 - Creating a TDSP Project.mp4
    06:04
  • 08 - Summary.mp4
    01:17
  • 09 - Overview.mp4
    01:09
  • 10 - Azure Machine Learning Workflow.mp4
    06:15
  • 11 - Launching a Notebook Server.mp4
    05:51
  • 12 - Leveraging Compute for Model Training.mp4
    02:26
  • 13 - Training a Model.mp4
    08:31
  • 14 - Deploying a Model.mp4
    06:10
  • 15 - Summary.mp4
    01:03
  • 16 - Overview.mp4
    01:17
  • 17 - Data Exploration And Reporting.mp4
    02:44
  • 18 - Utilizing the IDEAR Data Tool.mp4
    06:59
  • 19 - Machine Learning Pipelines.mp4
    04:06
  • 20 - Creating a Machine Learning Pipeline.mp4
    05:54
  • 21 - Azure Integration for Machine Learning.mp4
    02:56
  • 22 - Summary.mp4
    01:29
  • 23 - Overview.mp4
    01:05
  • 24 - Infrastructure for Machine Learning.mp4
    04:12
  • 25 - Deploying a Model with GPU Support.mp4
    05:22
  • 26 - Decommissioning Your Resources.mp4
    02:20
  • 27 - Summary.mp4
    01:08
  • Description


    This course will cover how to leverage Azure Machine Learning for a successful data science initiative across the key components of workflow, data pipeline, and infrastructure.

    What You'll Learn?


      When working on data science initiatives it can be challenging to gain actionable insights from your data set. In this course, Designing Machine Learning Solutions on Microsoft Azure, you will learn how to leverage Azure's Machine Learning capabilities to greatly increase the chance of success for your data science project. First, you will engage in team workflow and how Microsoft's Team Data Science Process (TDSP) enables best practices across disciplines. Next, you will discover the workflow of the Azure Machine Learning Service and how it can be leveraged on your project. After this, you will review how to create a pipeline for your data preparation, model training, and model registration. Finally, you will explore the infrastructure approaches that can be leveraged for machine learning and how those approaches are supported on Azure. When you are finished with this course, you will possess the skills that will be needed to start a data science project on Azure and the tools that will increase your ability to gain those actionable insights.

    More details


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    David Tucker
    David Tucker
    Instructor's Courses
    David is a Webby Award winning cloud development consultant that focuses on cloud native web, mobile, and IoT applications. For over fifteen years as a consultant David has led custom software development on emerging platforms for companies such as FedEx, AT&T, Sony Music, Intel, Comcast, Herman Miller, Principal Financial, and Adobe (as well as many others). David regularly writes and speaks on the digital landscape with published works for O'Reilly and Lynda.com. He has written for Mashable, Smashing Magazine, and VentureBeat, and he has spoken at events like AdTech, Interop, and Adobe Max.
    Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.
    • language english
    • Training sessions 27
    • duration 1:40:23
    • level average
    • Release Date 2023/12/05