This is my solution to the Kaggle Titanic Machine Learning Competition and I will be using python for this project.
For anyone not familiar with the Kaggle Titanic Machine Learning Competition, this dataset includes information on age, gender, class and more on passengers aboard the titanic as well as wether they survived or not.
The goal is to train a model to be able to predict a passenger will survive or not (classification). The data is split into a training set to train the model on and a test set to test the accuracy.
Starting out by importing required libraries:
As well as looking at the first few rows of the data, the column names and data types:
Using Panadas Profiling we can get a report on the dataset.
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