NUS DSESC Case Competition

Dataset Handling Guidelines

• The dataset is strictly for the purpose of this competition and should not be used for any other purposes.
• The dataset must not be shared with anyone outside of the competition, or uploaded to any repositories / cloud storage.

GitHub Repository Instructions

• The forked repository is public by default and it can't be made private. If you wish to collaborate on the project through GitHub, you can create a private repository and add your teammates as collaborators.
• Here is a set of instructions to create a private mirror of the repository.
• Make sure to make your repository public for your final submission.

Column Header Descriptions

• Column Header Name: Description

Submission Instructions

1. Rename the submission notebook as "NUS_DSESC_DATABUSTERS_XX.ipynb". For example, if your team name is "TEAM 01", your submission notebook should be named as "NUS_DSESC_DATABUSTERS_01.ipynb".
   The notebook already contains a template function, named testing_hidden_data, to take in the test data and output the predictions. You are to fill in the function with your model and any preprocessing function that you may have.
   Note: Each team should only submit one notebook and the notebook should be in the master branch.

2. You can save your model and upload it in the GitHub repository provided that it does not exceed the file size limit on GitHub (see Section 3 on instructions for large models). If you saved your model, you are to provide a script the load the model. Please name the loading function as load_model.
   If the model is not saved, we will assume that the model is trained using the training function and the output of the training model is a model that can be is trained using the template function, testing_hidden_data, provided in the notebook. Please name the training function as train_model.

3. If your model is too large to be uploaded to GitHub, you can upload it to Google Drive and share the link with us. Please ensure that the link is accessible by anyone with the link. Please provide a LOAD_MODEL_INSTRUCTIONS.md file in the GitHub repository to explain how to load the model. Note that you are strongly discouraged to use such large models.