#### 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 look like above?

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

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

#### Feature engineering

###### Can the notebook be executed without any error?

###### 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 close to what is expected?

#### Final score

###### Is the accuracy associated with the username in `username.txt` 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