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.

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

Visualize the RMS Titanic dataset in a Neo4j graph database.

Machine Learning from Titanic Disaster

Sopravviverai alla sciagura del Titanic? Un Classificatore Binario basato su Neural Network

Titanic Data Analysis

Simple EDA for Titanic Dataset.

Repository for Analysis of the Titanic problem on Kaggle.com

Process of Data Analysis of the famous Titanic dataset with Predict Model of survival

Kaggle Competition Question

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.

Introduction to AI and ML Course Project @NanyangTechnologicalUniversity

This analysis is about predicting the survival of a person onboard Titanic

Analyze the Titanic dataset to extract meaningful results.

This project aims to investigate the factors (Age, Class, Gender, etc)that contributed to survival in the tragic sinking of the Titanic and predict the survival chances of passengers based on some provided features.

So I decide to work through the insight of Titanic tragedy with a glance at the Data (famously) provided on Kaggle.

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

Estudo de Machine Learning usando dados reais do Titanic. Aula Ciencia de Dados do curso Carrefour Data Engineer.

This repo is for the queries I have been using to explore the Titanic dataset using SQL Server.

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

Este proyecto trabaja con el dataset del Titanic, aplicando técnicas de procesamiento y análisis de datos en Python con apoyo de la librería pandas. El objetivo es limpiar, transformar y estudiar las características disponibles, identificando valores faltantes, duplicados o atípicos, así como calcular métricas estadísticas relevantes.

Data Analysis on the RMS Titanic data set using Python

No description provided.

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

titanic dataset

This analysis focuses on finding answers about the chances of survival of the passengers of the Titanic tragedy on 1912

Predicts Titanic passenger survival using machine learning (Logistic Regression, Decision Tree, and Random Forest). Analyzes factors like age, gender, and fare to identify key predictors.

In this challenge, we'll build a predictive model that answers the question: “what sorts of people were more likely to survive to the Titanic tragedy?” using passenger data (name, age, gender, socio-economic class, etc).

Titanic survival analysis using Decision tree