Titanic Survival Prediction 🚢
This project analyzes the famous Titanic dataset and builds a predictive model to determine which passengers survived the disaster. Using Logistic Regression, we explore key features such as age, gender, and class to make predictions.
📂 Project Structure
LOGISTIC_REGRESSION.ipynb – Jupyter Notebook containing data analysis and model training
README.md – Project documentation
📊 Dataset
The dataset includes information on passengers, such as:
Passenger class
Sex
Age
Number of siblings/spouses aboard
Number of parents/children aboard
Fare price
🔍 Analysis & Approach
1.Exploratory Data Analysis (EDA) – Visualizing and understanding dataset
2.Feature Engineering – Selecting and preprocessing important features
3.Model Training – Using Logistic Regression to predict survival chances
4.Evaluation – Checking accuracy, precision, and recall of predictions