Titanic-ML-Challenge

This is a challenge on Kaggle to predict whether a person survives or not on the Titanic depending on the features given using Machine Learning

About

• I used different types of classifiers like DecisionTrees, KNearest-Neighbours and Gradient Boosting.
• I used cross-validation to increase the performance of the model i.e. to select the best algorithm.
• I also pre-processed the data to fill any null values present, encode non-numerical data and remove unwated features.
• I got 79.9% Accuracy using the Gradient Boosting algorithm.

Packages used

• scikit-learn
• Pandas
• Numpy
• matplotlib