Chapter 1: Introduction to scikit-learn

Activity 1: Selecting a Target Feature and Creating a Target Matrix

1. Load the titanic dataset using the seaborn library. First, import the seaborn library, and then use the load_dataset("titanic") function:

   import seaborn as sns
   titanic = sns.load_dataset('titanic')
   titanic.head(10)

   Next, print out the top 10 instances; this should match the below screenshot:

   Figure 1.23: An image showing the first 10 instances of the Titanic dataset

2. The preferred target feature could be either survived or alive. This is mainly because both of them label whether a person survived the crash. For the following steps, the variable chosen is survived. However, choosing alive will not affect the final shape of the variables.
3. Create a variable, X, to store the features, by using drop(). As explained previously, the selected target feature is survived, which is why it is dropped from the features matrix.

   Create a variable, Y, to store...