Titanic Disaster -- Who survived and who did not? This project aims at developing a model that predicts the fate of each passenger on the famous RMS Titanic that met a disaster and sank in Atalntic Ocean on 15 April 1912. The objective of this project is create different supervised machine learning algorithm in order to predict who survived and who did not? The model is trained on the data set in the Titanictrain.csv file using a subset of the given variables except survived variable which is the target variable. Once the model is developed, it will be used to predict the target variable from the data set in Titanictest.csv file and submit the resultant predictions to Kaggle in the format as provided in the gender_submission.csv file.

The project is done in python using the following libraries:

Pandas

Numpy

Sklearn

Used Tableau for EDA and Visualization. (https://public.tableau.com/profile/dhilip.subramanian#!/)

Below algorithms was applied in the analysis

1. Logistic Regression
2. Support Vector Machines
3. Random Forrest
4. Decision Tree
5. Stochastic Gradient Descent
6. K-Nearest Neighbours
7. XG Booster
8. Naive Bayes
9. Gradient Boosting Classifier