personal code for hyundai ship tag-mapping project
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Richard Wong 446ed1429c feat: end-to-end code needed for deployment that includes preprocess,
mapping, post-process (de-duplication)
2024-12-02 14:57:03 +09:00
analysis Feat: added more classification and mapping variations 2024-11-25 18:15:28 +09:00
data_import Chore: changed ipynb to py files in the data_preprocess folder 2024-10-29 22:55:22 +09:00
data_preprocess Chore: removed unnecessary output files 2024-11-25 18:19:52 +09:00
end_to_end feat: end-to-end code needed for deployment that includes preprocess, 2024-12-02 14:57:03 +09:00
evaluation Doc: updated README.md to reflect execution order 2024-10-31 16:51:47 +09:00
post_process feat: end-to-end code needed for deployment that includes preprocess, 2024-12-02 14:57:03 +09:00
train Feat: added de_duplication post-processing method 2024-11-28 11:02:22 +09:00
translation Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
.gitignore Chore: re-organized data_import directory to use .py files 2024-10-29 20:07:51 +09:00
README.md Doc: updated README.md to reflect execution order 2024-10-31 16:51:47 +09:00

README.md

hipom_data_mapping

Before we begin

This repository utilizes .py files rather than .ipynb for greater clarity.

If you use vscode, just use the ipython functionality from .py files.

In order to generate .ipynb file from .py file, you can do the following:

jupytext --to notebook your_script.py

Order of Execution

  • data_import: Import data from database
  • data_preprocess: Apply pre-process method
  • train: Train mapping model and apply model on test data
  • post_process: Apply post-processing method