bckhm / Titanic-ML

Classifying the survival of passengers aboard the Titanic via the use of various Machine Learning algorithms.

Titanic-ML

Binary classification of whether passengers aboard the Titanic survived, using various Machine Learning models. Based on Kaggle's Titanic - Machine Learning from Disaster competition.

Goal

"Knowing from a training set of samples listing passengers who survived or did not survive the Titanic disaster, can our model determine based on a given test dataset not containing the survival information, if these passengers in the test dataset survived or not."

Strategies Employed

Because of the need for classification the employed ML models are as follows: • Logistic Regressionm • Sigmoid-activated Neural Networks • Gradient Boosted Trees

We test the most optimal result for these models in the training set, before testing OOS.

Requirements

• Python 3
• TensorFlow
• numpy
• pandas
• matplotlib.pyplot
• seaborn
• xgboost
• sklearn
• Jupyter Notebook / Lab