What Is Automated Machine Learning? – Machine Learning Fundamental Concepts

What Is Automated Machine Learning?

Using automated machine learning, models can be easily created with no coding required. The most complicated models are hard to make, but they are useful for figuring out how well a standard model works for the first time or comparing different models. You have complete control over the primary metric, the number of models to run, the threshold, the number of cross-validations, the option to block the algorithm, and many other options.

Depending on the type of task, you can easily choose the algorithm from a menu that includes regression, classification, and time series. To enable deep learning, simply click the corresponding box.

You will be able to see the model’s specific explanations and metrics once it has been successfully deployed.

When data scientists use cloud-based computing resources that scale well to run multiple training experiments at the same time, automated machine learning makes them more efficient by automating many of the time-consuming tasks that come with training model components.

TipTo gain a better understanding of Microsoft Azure’s AI offerings, I recommend reading through each reference link in the book’s “References” section. These links will take you to the module’s Microsoft Learn training section.

Practical Labs

It’s time to get down to business. By following along with the practical lab here, you can see the whole process of making a machine learning model and learn about the different kinds of machine learning components and the linear regression technique in machine learning.

NoteThe purpose of the labs is to give you a solid understanding of Azure ML and the tools provided by Azure ML.

Using Azure Machine Learning Designer to Build a Regression Model

Sign in to your Azure Portal using your Azure subscription credentials.