Titanic Survival Prediction

Titanic Survival Prediction Using Machine Learning

Developed a machine learning project to predict the likelihood of passenger survival on the Titanic dataset using Python and the Random Forest Classification algorithm.

Project Features:

- Data preprocessing and handling missing values.

- Encoding categorical variables and applying feature scaling using StandardScaler.

- Training a Random Forest Classifier to predict passenger survival.

- Saving the trained model and scaler for future predictions.

- Developing an interactive web application using Flask, HTML, and CSS.

- Displaying the predicted survival outcome and estimated survival probability.

Technologies Used: Python, Pandas, NumPy, Scikit-learn, Flask, HTML, CSS, and Joblib.

Project Goal: To demonstrate practical skills in data preprocessing, machine learning model development, and deploying a predictive model through a web application.