Here’s part one of a series of blog posts that will explore the machine learning options available in Azure.

In this post series, I am going to show how we can use Azure Machine learning services and the new features added that make life so easy to train, deploy, automate managing machine learning models [1]. In this post, first I will show how to use a no code environment for Auto ML, how to access it and some difference between Azure mL Studio and services.

This video shows how to build, train and deploy a time series forecasting solution with Azure Machine Learning. You are guided through every step of the modeling process including:

  • Set up your development environment
  • Access and examine the data
  • Train using an Automated Machine Learning
  • Explore the results
  • Register and access your time series forecasting model through the Azure portal.