classification for titanic dataset using machine learning
تفاصيل العمل
on features such as age, gender, ticket class, fare, and family size. The project included data cleaning, handling missing values, feature encoding, exploratory data analysis, model training, and performance evaluation. Multiple classification algorithms were tested to compare accuracy and improve prediction results, with focus on understanding which factors most influenced survival outcomes. Key Steps Data preprocessing and cleaning Handling missing values Encoding categorical features Feature selection Model training Accuracy evaluation Model comparison Technologies Python Pandas NumPy Scikit-learn Matplotlib / Seaborn Jupyter Notebook
مهارات العمل
