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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