Machine learning is the ability of a machine to expand its knowledge without human intervention. The concept of machine learning is used in software engineering, in data mining, and, in particular, in artificial intelligence. Starting from a knowledge base rich in information, an automatic learning system searches and extracts any regularity between data through data mining techniques. Machine learning algorithms use mathematical-computational methods to learn information directly from the data, without mathematical models and predetermined equations.

The applications of machine learning are already numerous today, some of which have commonly entered our daily life without us realizing it. For example, search engines, through one or more keywords, return lists of results. Spam filters of emails continuously learn both to intercept suspicious or fraudulent email messages and to act accordingly. Finally, we have speech recognition systems or manual writing identification.

In this chapter, we will be introduced to the basic concepts of machine learning, and then we will take a tour of different types of algorithms. In addition, an introduction, some background information, and basic knowledge of the Microsoft Azure Machine Learning Studio environment will be covered. Finally, we will explore some practical applications to understand the amazing world of machine learning.

In this chapter, we will cover the following topics:

• Discovering the machine learning capabilities for classification, regression, clustering, and dimensionality reduction, including apps for automated model training and code generation
• A tour of the most popular machine learning algorithms to choose the right one for our needs
• Exploring the Azure Machine Learning Studio environment

By the end of this chapter, you will be able to recognize the different machine learning algorithms and the tools that Microsoft Azure Machine Learning Studio provides to handle them.