personal code for hyundai ship tag-mapping project
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Richard Wong c5760d127d Feat: added post_processing based on rules
others:
- added basic data analysis to get histograms of text differences
- added new final delivery model
2024-12-18 13:43:56 +09:00
analysis Feat: added post_processing based on rules 2024-12-18 13:43:56 +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 Feat: added post_processing based on rules 2024-12-18 13:43:56 +09:00
evaluation Doc: updated README.md to reflect execution order 2024-10-31 16:51:47 +09:00
interpretation Feat: added post_processing based on rules 2024-12-18 13:43:56 +09:00
post_process Feat: added post_processing based on rules 2024-12-18 13:43:56 +09:00
production Feat: added post_processing based on rules 2024-12-18 13:43:56 +09:00
train Feat: added post_processing based on rules 2024-12-18 13:43:56 +09:00
translation Chore: re-organized train folders to have standardized naming schemes 2024-11-20 15:07:47 +09:00
.gitignore Feat: added post_processing based on rules 2024-12-18 13:43:56 +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