This repository contains my analysis and machine learning model for predicting survival on the Titanic based on passenger data. The project was completed as part of my journey in data science. The analysis covers data preprocessing, exploratory data analysis (EDA), feature engineering, model selection, and evaluation.
data/: Folder containing the dataset files.notebooks/: Jupyter notebooks containing the analysis, visualization, and model development.images/: Images and visualizations used in this README.README.md: The file you're reading right now.
- Clone this repository:
git clone https://github.com/karrabi/titanic-project.git - Navigate to the repository:
cd titanic-project
notebooks/project_titanic_data_preparation.ipynb: Data loading, cleaning, and handling missing values.notebooks/project_titanic_EDA.ipynb: Visual exploration of data distribution and relationships.notebooks/project_titanic_ml.ipynb: Building and evaluating machine learning models.
- Python
- Jupyter Notebook
- Pandas, NumPy
- Matplotlib, Seaborn
- Scikit-learn
Summarize key insights and results from your analysis here.
Outline potential improvements you could make to the project in the future.
Give credit to any resources, tutorials, or inspiration you used during the project.
Feel free to contact me at a.karrabi@email.com.
Note: This project is for educational purposes and may contain code from tutorials, courses, or other sources.