Overfitting

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Machine learning is a notoriously complex subject that usually requires a great deal of advanced math and software development skills. That’s why it’s so amazing that Azure Machine Learning lets you train and deploy machine learning models without any coding, using a drag-and-drop interface. With this web-based software, you can create applications for predicting everything from customer churn rates to image classifications to compelling product recommendations.

In this lesson, you will learn the basic concepts of machine learning and then follow hands-on examples of choosing an algorithm, running data through a model, and deploying a trained model as a predictive web service.

Learning Objectives

  • Create an Azure Machine Learning workspace
  • Train a machine learning model using the drag-and-drop interface
  • Deploy a trained model to make predictions based on new data

Intended Audience

  • Anyone who is interested in machine learning

Prerequisites

  • General technical knowledge
  • A Microsoft Azure account is recommended (sign up for a free trial at https://azure.microsoft.com/free if you don’t have an account)

Resources

The GitHub repository for this lesson is at https://github.com/cloudacademy/azureml-intro.



About the Author
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Guy Hummel, opens in a new tab
Azure and Google Cloud Content Lead
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Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).

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