In this exercise, you will carry out a classification using the Titanic dataset from Kaggle. We used this dataset in the feature engineering exercise in Part 2.

https://www.kaggle.com/c/titanic

The following is a description of the features in the data:

You can find the code and data for this activity on the course GitHub repository.

The file  titanic_clean.csv  contains data that has already been cleaned up as follows:

• Nulls in Age have been imputed with the mean age.
• The first letter of the cabin has been split to provide a new deck feature.  This has then been one-hot encoded, with nulls going to a column Deck_nan.
• Sex has been one-hot encoded.
• Embarked has been one-hot encoded, with nulls going to a column Embarked_nan.

The Jupyter Notebook  classification_activity.ipynb  contains a template for the code you will run.  Open the template in Jupyter and write the code as guided within the template.  The objective is to predict the survival of passengers based on the available features.

Then answer the following questions.