In the previous chapters, we learned about the fundamentals of machine learning, and we learned how to build many different Python projects by using a suite of amazing open source Python libraries. Also, we dove into how to break machine learning models.
This last chapter will help you to build better models by illustrating many tips and best practices for different aspects of your projects.
In this chapter, we will cover the following:
- An in-depth overview of feature engineering in machine learning
- The best practices for machine learning
