Explonaratory data analysis and applied machine learning techniques on Titanic dataset which is provided from Kaggle.
I used 10 ML techniques which are :
* KNN
* Logistic Regression
* Gaussian Naive Bayes
* Support Vector Classifier
* Classification and Regression Trees
* Random Forest
* Gradient Boosting Machine
* Extreme Gradient Boost (XGBoost)
* Light GBM
* CatBoost
You can also download the dataset which is inside "dataset" file within a zip format.
For my submission with XGBoost on Kaggle competition, you can visit www.kaggle.com/asilkanv/titanic-eda-ml and look at the last part of notebook.
You can also contact me from my email : var-asilkan@hotmail.com