Predicting whether a new customer will churn

As you saw in the video, to train a model using sklearn:

• Import the model of interest - here, a Support Vector Classifier:

from sklearn.svm import SVC

• Instantiate it:

svc = SVC()

• Train it, or "fit it", to the data:

svc.fit(telco['data'], telco['target'])

Here, the first argument consists of the features, while the second argument is the label that we are trying to predict - whether or not the customer will churn. After you've fitted the model, you can use the model's .predict() method to predict the label of a new customer.

This process is true no matter which model you use, and sklearn has many! In this exercise, you'll use LogisticRegression.