Survival Predictor

Prepare · Predict · Perfect · Present

A machine-learning model that predicts the survival of the fittest.

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Table of Contents

• About the Project
• Results
• Technologies Used

About the Project

The Titanic Survival Predictor is a machine learning model that predicts whether a passenger would survive the Titanic disaster based on different features such as age, gender, and ticket class.

The project demonstrates:

• Data preprocessing and feature engineering.
• Logistic regression for survival prediction.
• Visualization of the correlation and survival analysis.

Visualizations include:

• Correlation Heatmap: To identify the most impactful features.
• Feature Distribution: To analyze how different features relate to survival.

Visual results include:

• Confusion Matrix: Understanding prediction errors.
• Learning Curve: Showing model improvement over time.
  

Results

Check on the website: here: Titanic Survival Predictor

Technologies Used

• Python
• Jupyter Notebook
• Logistic Regression
• Pandas, NumPy
• Matplotlib, Seaborn

Deployed Page

Visit the live deployment of the Titanic Survival Predictor here: Titanic Survival Predictor