From the course: Machine Learning with Python: Decision Trees

Using the exercise files - Python Tutorial

From the course: Machine Learning with Python: Decision Trees

Using the exercise files

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- [Instructor] The exercise files you need for this course will be provided to you. This means that you can follow along with any of the code examples in the lessons. I recommend that you do so. The best way to become proficient in building decision tree models in Python is to practice doing it yourself. The exercise files are organized into folders that correspond with the chapters of the course. Within each folder are data files and two notebooks for each of the code lessons. Let's take a look at an example. As you can see, folder 02 has a data file called loan.CSV. It also has two notebooks for the chapter two lesson videos. The 02B notebook is the beginning notebook. This is the notebook you should code in when following along with the lesson videos. The 02E notebook is the ending notebook. It is a completed version of the beginning notebook for your reference. There are several ways to launch a notebook. One approach is to launch the Anaconda Navigator, click on Launch Jupyter Notebook, then navigate to the notebook you want and launch it. Let's do this together. Depending on how fast or how resourced your computer is, this may take a while, or it may happen very quickly. Now that we have Anaconda Navigator open, let's click on Launch Notebook. Then we go to the folder, find the exercise files, and now we can launch our notebook.

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