11. Machine Learning

Activity 25: Using Machine Learning to Predict Customer Return Rate Accuracy

Solution:

1. The first step asks you to download the dataset and display the first five rows.

   Import the necessary pandas and numpy libraries to begin with:

   import pandas as pd
   import numpy as np

2. Next, load the CHURN.csv file:

   df = pd.read_csv('CHURN.csv')

3. Now, display the headers using .head():

   df.head()

   You should get the following output:

   Figure 11.37: Dataset displaying the data as output

4. The next step asks you to check for NaN values. The following code reveals that there are none:

   df.info()

   You should get the following output:

   Figure 11.38: Information on the dataset

5. The next step is done for you. The following code converts 'No' and 'Yes' into 0 and 1:

   df['Churn'] = df['Churn'].replace(to_replace=['No', 'Yes'], value=[0, 1])

6. The next step asks you to correctly define X and y. The correct solution...