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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

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