synthanic_competition

This is the solution for the Synthanic competition on Kaggle.

The goal is to perform EDA and create a model solving binary classification task using synthetic dataset which is based on a real Titanic dataset. The statistical properties of this dataset are similar to the original (and well known) Titanic dataset.

Accuracy score on test set:

The notebook with solution contains:

1. Data quality assessment and missing data imputation.
2. Thorough Data exploration with many plots, observations, summary and feature engineering.
3. Modeling block were I compared 3 algorithms: Logistic Regression, KNN and Random Forests and did model tuning with RandomizeSearchCV, cross validation, feature selection, data scaling and encoding.