/Kaggle_Titanic_Tutorial

A tutorial article of Kaggle Titanic competition that contains extensive EDA

Primary LanguageJupyter Notebook

Titanic - How EDA Helps You Gets High Scores

Python, Numpy, Pandas, Scikit-Learn Data Leakage, EDA, Feature Engineering, Machine Learning, Class Imbalance, Missing Value Imputation

Project Description

This is an tutorial article drafted for ML beginners that cover key concepts in ML includes data leakage, Class Imbalance. The main focus of this article is EDA. It explains why good EDA helps you select good features, discover hidden features, and improve your score on Kaggle.

You can read the article by clicking on the .ipynb file, or read it on Kaggle .here