Titanic: Machine Learning from Disaster – Kaggle Competition Solution using Python

Kaggle is an online platform that hosts different competitions related to Machine Learning and Data Science.

Titanic is a great Getting Started competition on Kaggle. This is one of the highly recommended competitions to try on Kaggle if you are a beginner in Machine Learning and/or Kaggle competition itself.

This competition contains the dataset of passengers who were in the Titanic ship that sank on April 15, 1912, A.D. Out of 2224 passengers, 1502 were killed in the accident. The challenge of the competition is to predict the survival of passengers on the Titanic ship. Machine Learning techniques are to be applied to predict which passenger survived and which did not.

The Titanic competition solution provided below also contains Explanatory Data Analysis (EDA) of the dataset provided with figures and diagrams.

Python programming language is being used.

The following Machine Learning Classifiers are analyzed by observing their classification accuracy:

– Logistic Regression
– Support Vector Machines (SVC)
– Linear SVC
– k-Nearest Neighbor (KNN)
– Decision Tree
– Random Forest
– Naive Bayes (GaussianNB)
– Perceptron
– Stochastic Gradient Descent (SGD)

Titanic Kernel on Kaggle | Kaggle Competitions Solution on GitHub

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Hope this helps. Thanks.