Hello, and welcome.
In this lesson, you learn how to train and publish a regression 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 regression model, use a regression model
for inferencing, and deploy a regression
model as a service. Earlier in this course, you explored machine learning. Machine learning uses algorithms to identify patterns within data, and those patterns
are then used to create a data model that
can make predictions. Regression is a form of machine
learning that is used to predict a numeric label
based on an item's features. For example, an automobile
sales company might use the characteristics of an
auto such as engine size, number of seats, mileage, and so on to predict its
likely selling price. In this case, the
characteristics of the car are the features and the
selling price is the label. Regression is an example of a supervised machine
learning technique in which you train
a model using data. The data includes both the features are known
values for the label so that the model learns to fit the feature combinations
to the label. Then after training
has been completed, you can use the train
model to predict labels for new items for
which the label is unknown. You can use Microsoft Azure Machine Learning
designer to create regression models by
using a drag and drop visual interface without
needing to write any code.