Building a Model
Follow step-by-step instructions to explore the German Credit dataset and build a predictive model.
We'll cover the following...
Exploratory data analysis
Before we build the model, we need to perform exploratory data analysis. We are going to load it and go feature-by-feature in order to understand its meaning and characteristics. During this stage, we will try to identify sensitive attributes and important features that can be used for modeling. The most important questions we need to answer are:
How many observations do we have?
Is the dataset balanced?
What are the number and types of features?
In addition, we perform simple data processing for further modeling.
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