From the course: Machine Learning with Python: Decision Trees

What you should know - Python Tutorial

From the course: Machine Learning with Python: Decision Trees

What you should know

“

- [Instructor] Before we get started, let's go over some of the background knowledge that you should have in order to get the most out of this course. First, I assume that you have a fundamental understanding of what machine learning is, specifically supervised machine learning. If you don't, I recommend that you review my introductory LinkedIn Learning course, Machine Learning with Python: Foundations. Second, it will be helpful if you have some entry level knowledge coding in Python I will assume that you know how to import a Python package, refer to attributes of an object and call the methods of an object. Next, it would also be helpful if you have some familiarity with the pandas and scikit-learn packages. If you don't, no worries. I will explain exactly what I'm doing when we do use these packages in the course. Finally, I do assume that you know how to use the Jupyter Notebook interactive Python environment. Specifically, I assume that you know how to create a code cell as well as how to edit and run code within a code cell.

Contents