#### 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
