Hello and welcome.
In this lesson, you'll learn how to train and publish a clustering model with Microsoft Azure Machine
Learning Designer without needing to
write any code. By the end of this lesson, you'll be able to use Azure Machine Learning Designer to train a clustering model, use a clustering model for inferencing and deploy a
clustering model as a service. Clustering is a form of machine
learning that is used to group similar items into clusters based on their features. For example, a researcher
might take measurements of penguins and group them based on similarities in
their proportions. In Microsoft Azure
Machine Learning, data from model training
and other operations is usually encapsulated in an
object called a dataset. In this lesson, you'll
use a dataset that includes observations of
three species of penguin. Earlier in this course, you explored regression which is an example of a supervised
machine learning technique. Using this technique, you
trained a model using data that includes both the features and known values for the label. In this lesson, you'll focus on unsupervised machine learning. Clustering is an example of unsupervised machine learning in which you train a model to separate items into clusters based purely on their
characteristics or features. There is no previously
known cluster value or label from which
to train the model. You can use Azure Machine
Learning Designer to create clustering models by using a drag and drop visual interface without
needing to write any code.