Start here if... You're new to data science and machine learning, or looking for a simple intro to the Kaggle prediction competitions. Competition Description The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy. Practice Skills Binary classification Python and R basics

Using Machine learning algorithm on the famous Titanic Disaster Dataset for Predicting the survival of the passenger.

Udacity Machine Learning Nano degree Program Project Predicting Passenger Survival

Titanic Survival prediction: Titanic dataset- how many people survive and how many were Male and Female

Some useful examples of Deep Learning (.ipynb)

Surviving the Titanic step-by-step with groups

🚢 Association and Pattern Recognition Algorithms on data from Titanic survivors.

Titanic Survival Prediction using Logistic Regression

Titanic Survival Exploration & Prediction - 1st project for Udacity's Machine Learning Nanodegree

Investigate Titanic Dataset Using iPython Notebook, Pandas, Matplotlib, and Seaborn

Solution to the titanic machine learning competition on kaggle

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Maximum entropy (MaxEnt) classifier

Kaggle Competition - Titanic: Machine Learning from Disaster (Top 8%)

This short project take the Titanic Survival Data Set and Analyze it.

This project aims to predict the survival of passengers aboard the Titanic using the Naive Bayes classifier algorithm. The dataset used in this project contains information about Titanic passengers, such as their age, gender, passenger class, and other relevant features.

Contains project work for Udacity's Data Analyst Nanodegree from the September 2017 cohort

🚢 Titanic survival outcomes using various classification. It includes comprehensive approach to data preprocessing, training, and evaluation.

Visualization of the Titanic DataSet

Predict the survival rate and Chances get Survived on Titanic using Machine learning.

This Repository contains the Titanic Survival Project created by using Logistic Regression in Machine Learning.

Explore Titanic survival data by implementing a decision tree in sci-kit-learn

Prediction of Survivors from titanic data set.

LITG project

Detailed Exploratory Data Analysis (EDA) of the Titanic dataset.

A data-driven analysis and machine learning model to predict passenger survival in the Titanic disaster using Python, Pandas, and Scikit-learn.

Udacity - Machine Learning Engineer Nanodegree Project - Titanic Survival Exploration

This repository shows the Passenger Survival Prediction of titanic dataset.

Titanic

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