Azure Data Scientist Associate: Azure Machine Learning Workspaces

Azure    |    Intermediate
  • 9 videos | 59m 18s
  • Includes Assessment
  • Earns a Badge
Rating 4.6 of 8 users Rating 4.6 of 8 users (8)
Azure Machine Learning workspaces provide an environment for performing experiments and managing data, computer targets, and other assets. Other assets can include notebooks, pipelines, and trained models. This course will focus on using the Azure Machine Learning SDK. In this course, you'll learn to create an Azure Machine Learning workspace by creating a machine learning resources, creating compute resources, and cloning a notebook. Next, you'll examine how to install the Machine Learning SDK for Python and create code to connect to a workspace. You'll learn to create Python scripts to run an experiment, log metrics, and retrieve and view logged metrics. Finally, you'll examine how to use the Azure Machine Learning SDK to run code experiments, create a script to train a model, and run a notebook using Jupyter to train predictive models. 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 the features and components of the azure machine learning workspace
    Create an azure machine learning workspace and resource group using azure portal and use azure machine learning studio to create a compute resource, and clone a notebook
    Install the machine learning sdk for python and create code to connect to a workspace
    Create python scripts to run an experiment, log metrics, and retrieve and view logged metrics
  • Use the azure machine learning sdk to run code experiments that log metrics and generate outputs
    Create a script to train a model, add parameters to the script, and run the object to get the training model
    Run a notebook using jupyter to train predictive models
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 38s
  • 9m 51s
  • Locked
    3.  Creating an Azure Machine Learning Workspace
    7m 27s
  • Locked
    4.  Installing Azure Machine Learning Tools
    6m 13s
  • Locked
    5.  Creating Scripts for Machine Learning Experiments
    6m 23s
  • Locked
    6.  Using Azure Machine Learning Metrics
    6m 56s
  • Locked
    7.  Creating Scripts for Azure Machine Learning Training
    8m 36s
  • Locked
    8.  Running a Notebook to Train Predictive Models
    11m 26s
  • Locked
    9.  Course Summary
    48s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Course Azure AI Fundamentals: Working with Azure Machine Learning Studio
Rating 5.0 of 9 users Rating 5.0 of 9 users (9)
Course Microsoft Azure Fundamentals: Software Development Services
Rating 4.5 of 208 users Rating 4.5 of 208 users (208)
Course Azure Data Scientist Associate: Machine Learning Services
Rating 4.7 of 18 users Rating 4.7 of 18 users (18)

PEOPLE WHO VIEWED THIS ALSO VIEWED THESE

Course AWS Certified Machine Learning: Machine Learning in SageMaker
Rating 4.3 of 134 users Rating 4.3 of 134 users (134)
Course Azure Data Scientist Associate: Machine Learning Regression Models
Rating 4.1 of 7 users Rating 4.1 of 7 users (7)
Course Azure Data Scientist Associate: Machine Learning
Rating 4.6 of 40 users Rating 4.6 of 40 users (40)