Python Artificial Intelligence Projects for Beginners

Prediction involving decision trees and
student performance data
In this section, we're going to use decision trees to predict student performance using the
students, past performance data. We'll use the student performance dataset, which is
available on the UC Irvine machine learning repository at 
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. Our final goal is to predict whether the student has
passed or failed. The dataset contains the data of about 649 students, with and 30 attributes
for each student. The attributes formed are mixed categorically 
b
 word and phrase, and
numeric attributes. These mixed attributes cause a small problem that needs to be fixed. We
will need to convert those word and phrase attributes into numbers.
The following screenshot shows the  first half of the attributes from the data:

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Building Your Own Prediction Models
Chapter 1
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You must have noticed how some of the attributes are categorical, such as the name of the
school;