Summary

In this chapter, we explored the amazing world of machine learning and took a tour of the most popular machine learning algorithms to choose the right one for our needs. To understand what is most suitable for our needs, we learned to perform a preliminary analysis. Then we analyzed how to build machine learning models step by step. 

Afterwards, we discovered the machine learning capabilities in MATLAB for classification, regression, clustering, and deep learning, including apps for automated model training and code generation. We verified the MATLAB system requirements and platform availability for a correct installation.

Finally, we introduced the Statistics and Machine Learning Toolbox and Neural Network Toolbox. We learned what we can do with these tools, and what algorithms we need to use to solve our problems. We understood the role of statistics and algebra in machine learning and how MATLAB can help us.

In the next chapter, we will learn how to easily interact with the MATLAB workspace, import and organize our data in MATLAB, export data from the workspace, and organize the data in the correct format for the next phase of data analysis.