I have used machine learning concept to analyze the Titanic dataset and predict survival rate with 94% accuracy.

I started this project by doing some exploratory data analysis(EDA), using seaborn and matplotlib libraries to create visualizations, check missing data, which features are important and understand better the dataset.

During feature engineering and data processing, I computed missing values, converted features into numeric ones, grouped values into categories, and created new features . Afer, I trained 7 different machine learning models, picked the best one (Random Forest), and applied cross validation on the model. I identified which features assign the most importance and tuned its performance through hyperparameter optimization. Lastly, I looked at Confusion Matrix and computed the models precision, recall and predicting with 94% accuracy using the ROC AUC Score.

Conclusion: I'am really glad to do this project as I learned valuable concepts that can be transferable to others project.Looking forward to keep learning new things and tacking new projects in my Machine Learning journey.