Learn how to use the Azure machine learning service and what features it offers to conduct routine machine learning tasks to solve network security problems.
- [Instructor] Azure is a Microsoft answer to cloud computing. Among the many services provided by Azure is a machine learning service, as part of its predictive analytics services. Azure Machine Learning, or ML, provides an intuitive graphical user interface, to guide a user through a machine learning process. It consists of data processing modules, machine learning algorithms, and Application Program Interface, or API, to expose feature models to applications.
More specifically, ML Studio is a comprehensive user interface, used to control a machine learning process from beginning to end. That is through it, an end user can invoke, pre-processing for raw data, train a machine learning algorithm, and help develop an effective feature model. ML Studio also allows its users to deploy the trained feature model to Azure. The ML Azure API is what gives programmers access to the selected feature model, once it is deployed to an Azure cloud service environment.
Let's see what ML Studio actually looks like. As you can see, it offers a drag and drop capability. You can intuitively connect components such as datasets, pre-processing modules, and machine learning algorithms, to create your own design for a certain process flow. Executing the completed process is as simple as clicking on a Play button. So I know what you're seeing is this experiment running, in the Microsoft Azure Machine Learning Studio.
And because it's running, it doesn't show the Play button. It only shows the Stop button. But when there's no experiment running, you will be able to see the Play button. The nice thing about the Azure ML service is its simplicity, which allows you to quickly learn how to use machine learning algorithms, to solve your real live problems, without having to know all the ins and outs of the machine learning theory. Are you ready to try it out yourself?
- Network security concepts
- The basic functions of a firewall
- Intrusion detection and prevention systems
- Using network data to improve security
- Using log servers to collect data
- Collecting application data
- Collecting OS data
- Network forensics
- Network security visualization