#### First Kaggle: Titanic

##### Preliminary

```
project
│   README.md
│   environment.yml
│   username.txt
│
└───data
│   │   train.csv
│   |   test.csv
|   |   gender_submission.csv
│
└───notebook
│   │   EDA.ipynb
|
|───scripts
│

```

###### Does the structure of the project is as below ?

###### Does the readme file give an introduction of the project, show the username, describe the feature engineering and show the best score the on the leaderboard ?

###### Does the environment contain all libraries used and their versions that are necessary to run the code ?

##### Feature engineering

###### Does the notebook can be executed without any arror ?

###### Does the notebook explain the feature engineering that contributed to improve the accuracy ?

##### Scripts

###### Can you train the best model on the train data with feature engineering without any error ?

###### Can you predict on the test set using the best model without any error ?

###### Is the score you get **on the test set** with the best model is close to what is expected ?

##### Final score

###### Is the accuracy associated with the username in `username.txt` is higher than 79% ? The best submission score can be accessed from the user profile.

##### Examples

Here are two very good submissions explained and detailed:

- https://www.kaggle.com/konstantinmasich/titanic-0-82-0-83
- https://www.kaggle.com/sreevishnudamodaran/ultimate-eda-fe-neural-network-model-top-2