In this chapter, we have gone through the basics of machine learning. We briefly discussed how machine learning fits into daily use cases and its relationship with the cybersecurity world. We also learned the different aspects of data that we need to know to deal with machine learning. We discussed the different segregation of machine learning and the different machine learning algorithms. We also dealt with real-world platforms that are available on this sector.
Finally, we learned the hands-on aspects of machine learning, IDE installation, installation of packages, and setting up the environment for work. Finally, we took an example and worked on it from end to end.
In the next chapter, we will learn about time series analysis and ensemble modelling.
