CatBoost tutorials repository

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 150…

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

SPPU BE COMP LP3 Codes - Machine Learning (ML) and Information and Cyber Security (ICS)

The following repository contains source code for a 100 Day personal machine learning coding challenge. It contains projects that I do as a part of my learning

Exploring the World's Most Renowned Shipwreck 🚢

Some algorithms of machine learning like Regression, Cluster, Deep Learning, and much more.

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

Welcome to the Titanic Classification project repository! This project aims to predict whether a passenger on the Titanic survived or not based on various features such as age, gender, class, and more.

Project for Titanic survival prediction, achieving 83.28% accuracy through advanced feature engineering, hyperparameter optimization, and ensemble methods.

Testing different ML models on famous Titanic dataset from kaggle. (100% accuracy)

Repository for Data Science and Visualization

Data visualization tool for the Titanic dataset developed in Unity3D for the course Interaction in Mixed Reality Spaces at the University of Konstanz.

Predicting the survival of passengers on RMS Titanic using information about the passengers.

Solution to titanic competition on kaggle

Digging for Data ⛏️

Titanic datasets exercises

Titanic Survival Prediction using Machine Learning predicts whether a passenger survived based on features like age, gender, and class. A Random Forest Classifier achieved 82.68% accuracy after data preprocessing. Explore this project to see how machine learning handles this classic problem.

The machine learning model is trained utilizing the LightGBM algorithm based on the "Spaceship Titanic" dataset.

XGBoost classification model predicting Titanic passenger survival with data preprocessing, feature engineering, and SMOTE for class balancing. Developed for the Kaggle Titanic competition.