This project uses the Kaggle Titanic dataset to predict passenger survival. It includes data cleaning, exploratory data analysis, feature engineering, model training, and performance comparison of multiple classification algorithms such as Logistic Regression, KNN, Decision Tree, Naive Bayes, and SVM.
From the README
🚢 Titanic Survival Prediction using Machine Learning 📌 Project Overview This project aims to predict whether a passenger survived the Titanic disaster using supervised machine learning techniques. The workflow covers the complete machine learning pipeline, including data preprocessing, exploratory data analysis (EDA), feature engineering, model training, evaluation, and comparison of multiple classification algorithms. The objective is not only to build an accurate predictive model but also to compare the performance of different machine learning algorithms using standard evaluation metrics. --- 🎯 Objectives • Perform data cleaning and preprocessing. • Explore the dataset to...
Skills
- Jupyter Notebook
