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The Machine Learning Workshop

You're reading from   The Machine Learning Workshop Get ready to develop your own high-performance machine learning algorithms with scikit-learn

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839219061
Length 286 pages
Edition 2nd Edition
Languages
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Author (1):
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Hyatt Saleh Hyatt Saleh
Author Profile Icon Hyatt Saleh
Hyatt Saleh
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Toc

1. Introduction to Scikit-Learn

Activity 1.01: Selecting a Target Feature and Creating a Target Matrix

Solution:

  1. Load the titanic dataset using the seaborn library:
    import seaborn as sns
    titanic = sns.load_dataset('titanic')
    titanic.head(10)

    The first couple of rows should look as follows:

    Figure 1.22: An image showing the first 10 instances of the Titanic dataset

  2. Select your preferred target feature for the goal of this activity.

    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 that's been chosen is survived. However, choosing alive will not affect the final shape of the variables.

  3. Create both the features matrix and the target matrix. Make sure that you store the data from the features matrix in a variable, X, and the data from the target matrix in another variable, Y:
    X = titanic.drop('survived',axis = 1)
    Y = titanic...
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