titanic

机器学习项目实战

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.

Spark ML Tutorial and Examples for Beginners

This repository contains a gentle introduction to machine learning algorithms with hands on practical examples

Kick-off repository for starting with Kaggle!

I used expert mode of TensorFlow to solve some problems

This repository is on different types of data, types of missing values and how to handle missing value

A complete end-to-end data science pipeline for the classic Kaggle Titanic competition. Featuring data cleaning, feature engineering, and predictive modeling using Scikit-Learn.

Survival prediction using Titanic dataset and Logistic Regression

Some useful examples of Deep Learning (.ipynb)

Kodluyoruz istatistik ve veri ön işleme çalışma grubunda Eğitmenimiz tarafından önerilen Titanic veri seti üzerindeki çalışmam yer almaktadır. Bu çalışmada veri setinin betimsel istatistikleri, veri görselleştirmesi, eksik (kayıp) veri analizi yöntemleri (missing value analysis methods) , aykırı değer analizi (outlier detection) yöntemleri ilgil…

Predict survival on the Titanic on a Quantum Computer

Data Analysis Solution for Titanic passenger data.

東京大学グローバル消費インテリジェンス寄付講座

🚢 Kaggle Titanic ML solution achieving 0.80143 score using 100-model ensemble of Gradient Boosted Trees | TensorFlow Decision Forests

find things in google maps

Exploratory data analysis (EDA) of the Titanic dataset using Python. Analyzed survival patterns by age, gender, and class with visualizations (seaborn/matplotlib). Non-ML focus—highlighting insights with statistics and plots.

Deep learning (TabFormer) experiment for the Kaggle Titanic ML competition - binary survival prediction.

Task 2 of the Prodigy infotech Data science internship