kaggle-titanic and Titanic_Rescue_Prediction

kaggle-titanic
51
Established
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 9/25
Maturity 8/25
Community 14/25
Stars: 949
Forks: 677
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 73
Forks: 10
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About kaggle-titanic

agconti/kaggle-titanic

A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.

This project provides a detailed example of how to analyze historical data to predict outcomes using machine learning. It takes raw passenger data from the Titanic disaster and guides you through cleaning, visualizing, and applying predictive models. Aspiring data analysts or data scientists new to Python will find this useful for understanding competitive data analysis workflows.

data-analytics-education predictive-modeling-tutorial historical-data-analysis machine-learning-beginners data-science-competitions

About Titanic_Rescue_Prediction

zmzhouXJTU/Titanic_Rescue_Prediction

Kaggle入门级机器学习项目:泰坦尼克号生存预测

This project helps anyone interested in historical data analysis understand which factors contributed to a person's survival during the Titanic disaster. By analyzing passenger attributes like age, gender, and class, it identifies patterns and predicts survival outcomes. The input is raw passenger data, and the output is a prediction of whether a specific passenger would have survived.

historical-data-analysis maritime-history survival-prediction social-stratification data-storytelling

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