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#### 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