🚢 Passenger Survival Prediction on the Titanic

Predicting passenger survival on the Titanic using machine learning techniques. This project aims to analyze various passenger features to build a predictive model.

Explore the Project Notebooks

Table of Contents

• About the Project 💻
• Project Workflow 📚
• Built With 🖥️
• Getting Started 🚀
  • Prerequisites 📋
  • Installation 📋
• Usage 📋
• Contributing 🤝
• License 📄
• Acknowledgements 🙏
• Contact ☎️

About the Project 💻

The sinking of the RMS Titanic is a well-known historical tragedy. This project leverages machine learning to predict whether a passenger survived based on features like age, sex, class, and family relations. It's a classic introductory project for anyone diving into data science and predictive modeling.

Key aspects of this project:

• Data cleaning and preprocessing.
• Exploratory Data Analysis (EDA) to understand the dataset.
• Feature engineering to improve model performance.
• Training and evaluating various machine learning models.

Project Workflow 📚

1. Data Collection and Overview:

   • Gathering the Titanic dataset and understanding its structure.

2. Data Preprocessing and Cleaning:

   • Handling missing values, outliers, and converting categorical data.

3. Exploratory Data Analysis (EDA):

   • Visualizing data, identifying patterns, and understanding feature relationships.

4. Feature Engineering:

   • Creating new features (e.g., family size, title extraction) to enhance model accuracy.

5. Model Selection and Training:

   • Splitting data into training and testing sets.
   • Training models like Logistic Regression, Random Forests, and Gradient Boosting.

6. Model Evaluation and Performance Metrics:

   • Evaluating models using metrics like accuracy, precision, recall, and F1-score.
   • Hyperparameter tuning for optimal performance.

7. Conclusion and Results:

   • Summarizing model performance and identifying important features.

Built With 🖥️

• Python
• Pandas
• NumPy
• Scikit-learn
• Matplotlib
• Seaborn

Getting Started 🚀

Follow these steps to set up the project locally.

Prerequisites 📋

• Python 3.x installed.
• Pip package manager.

Installation 📋

1. Clone the repository:

   git clone [https://github.com/YourUsername/titanic-survival-prediction.git](https://www.google.com/search?q=https://github.com/YourUsername/titanic-survival-prediction.git)

2. Navigate to the project directory:

   cd titanic-survival-prediction

3. Create a virtual environment (recommended):

   python3 -m venv venv
   source venv/bin/activate  # On macOS and Linux
   venv\Scripts\activate  # On Windows

4. Install the required packages:

   pip install -r requirements.txt

5. Run the jupyter notebook

   jupyter notebook titanic_notebook.ipynb