personal code for hyundai ship tag-mapping project
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Richard Wong 7699201cb8 Feat: implement selection for pattern-mapping
Feat: added error analysis for BERT find-back
Feat: added direct mapping with unit
Feat: added BERT for classification using description only
2024-11-11 20:20:43 +09:00
analysis Feat: implement selection for pattern-mapping 2024-11-11 20:20:43 +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: implement selection for pattern-mapping 2024-11-11 20:20:43 +09:00
evaluation Doc: updated README.md to reflect execution order 2024-10-31 16:51:47 +09:00
post_process Feat: implement selection for pattern-mapping 2024-11-11 20:20:43 +09:00
train Feat: implement selection for pattern-mapping 2024-11-11 20:20:43 +09:00
translation Chore: moved selection to post_process, mapping to test 2024-10-31 16:35:28 +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