https://github.com/prashver/titanic-survival-prediction

This project tackles the Titanic challenge on Kaggle, predicting passenger survival based on variables like age, sex, and passenger class. The Jupyter notebook covers essential steps of a data science pipeline, including exploratory data analysis, data cleaning, feature engineering, and modeling. The dataset used is the Titanic dataset.
https://github.com/prashver/titanic-survival-prediction

classification-algorithm machine-learning-algorithms matplotlib numpy pandas scikit-learn seaborn

Last synced: about 18 hours ago
JSON representation

This project tackles the Titanic challenge on Kaggle, predicting passenger survival based on variables like age, sex, and passenger class. The Jupyter notebook covers essential steps of a data science pipeline, including exploratory data analysis, data cleaning, feature engineering, and modeling. The dataset used is the Titanic dataset.

• Host: GitHub
• URL: https://github.com/prashver/titanic-survival-prediction
• Owner: prashver
• Created: 2022-05-12T11:24:07.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2022-05-27T08:13:02.000Z (over 2 years ago)
• Last Synced: 2024-11-14T17:12:04.058Z (2 months ago)
• Topics: classification-algorithm, machine-learning-algorithms, matplotlib, numpy, pandas, scikit-learn, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 266 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Titanic-Survival-Prediction

The Titanic challenge on Kaggle is a competition in which the task is to predict the survival or the death of a given passenger based on a set of variables describing him such as his age, his sex, or his passenger class on the boat. 

In a form of a jupyter notebook, my solution goes through the basic steps of a data science pipeline:

- Exploratory data analysis with visualizations

- Data cleaning

- Feature engineering

- Modeling

# Dataset used: [Titanic dataset](https://www.kaggle.com/competitions/titanic)