ML Classification Model for Predicting Passenger Survival Rates
Developed during my Data Science internship at CodSoft (Aug-Sep 2023), this machine learning project predicts passenger survival rates on the Titanic using classification algorithms. The project demonstrates end-to-end ML workflow from data preprocessing to model deployment.
GitHub Repository: github.com/AliMusharafbaig/CodSoft
Loaded Titanic dataset, performed exploratory data analysis (EDA), visualized distributions
Handled missing values, encoded categorical variables, scaled features
Created new features, selected important variables, reduced dimensionality
Trained multiple classifiers (Logistic Regression, Random Forest, SVM)
Cross-validation, accuracy metrics, confusion matrices, ROC curves
Exploratory data analysis to understand patterns and relationships in historical data
Creating meaningful features from raw data to improve model performance
Comparing different ML algorithms to find the best performer for the task
Using proper metrics to assess and validate model accuracy and generalization