Applied AI Project - Titanic Survival Analysis

This repository contains my Applied AI Project, where I analyze the Titanic dataset to predict passenger survival using machine learning techniques.

Files

• TitanicAnalysis.ipynb: Jupyter Notebook with complete analysis and implementation.
• TitanicAnalysis.html: HTML version of the notebook for easy viewing in a browser.
• titanic.xls: The Titanic dataset was used for the analysis.
• Requiremnets.txt: List of required Python libraries.

Project Highlights

• Data Preprocessing:
  • Handled missing values and encoded categorical features.
  • Conducted exploratory data analysis to uncover patterns.
• Machine Learning:
  • Implemented Logistic Regression and Decision Tree models.
  • Evaluated models using accuracy, precision, and recall metrics.
• Visualization:
  • Used Matplotlib to create insightful charts and graphs.

How to View

• Open TitanicAnalysis.html in any web browser for a quick overview.
• Alternatively, run the TitanicAnalysis.ipynb notebook after installing the required libraries listed in Requiremnets.txt.

Technologies Used

• Python: Pandas, Scikit-learn, Matplotlib
• Jupyter Notebook for analysis and visualization

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Feel free to explore and reach out with any questions or feedback!