Titanic Survival prediction: Titanic dataset- how many people survive and how many were Male and Female
-
Updated
Apr 12, 2022 - Jupyter Notebook
Titanic Survival prediction: Titanic dataset- how many people survive and how many were Male and Female
Predict who is likely to have survived in the titanic crash given his/her information
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.
How to perform an exploratory data analysis on the Kaggle Titanic dataset.
Start here! Predict survival on the Titanic and get familiar with ML basics.This is the legendary Titanic ML competition – the best, first challenge for you to dive into ML competitions and familiarize yourself with how the Kaggle platform works.
The goal of this project is predicting the survival of passengers based on a set of data. Necessary data is retrieved from Kaggle competition "Titanic: Machine Learning from Disaster".
Data analysis and Machine learning on titanic data
TOP13% solution for the Titanic-Kaggle competition using a Gradient Boosting Classifier. Moreover, implementation of a Streamlit App to play with the models.
In this code we will predict survived for the tragic accident Titanic. It's a Kaggle competition.
Kaggle Machine Learning Competition
Detailed Exploratory Data Analysis (EDA) of the Titanic dataset.
Data Science internship at Asterisc Technocrat Pvt. Ltd. Task - Billioniaire Analysis, Covid - 19 Data Analysis, Titanic Survival Prediction
Add a description, image, and links to the titanic-machine-learning topic page so that developers can more easily learn about it.
To associate your repository with the titanic-machine-learning topic, visit your repo's landing page and select "manage topics."