In this chapter, we'll make a quick revision of the essential machine learning topics. Topics such as supervised machine learning are covered, alongside the basic concepts of regression and classification.
We will understand why machine learning is essential for success in the 21st century from various perspectives: those of students, professionals, and business users, and we will discuss the different types of problems machine learning can solve.
Further, we will introduce the concept of automation and understand how it applies to machine learning tasks. We will go over automation options in the Python ecosystem and compare their pros and cons. We will briefly introduce the TPOT library, and discuss its role in the modern-day automation of machine learning.
This chapter will cover the following topics:
- Reviewing the history of machine learning
- Reviewing automation
- Applying automation to machine learning
- Automation options for Python