A tool for matching student interests to areas of study.
- Set up python environment:
conda env create --file environment.yml
conda activate csc-570
embeddings
: Sklearn-style transformers that encode natural language into latent embedding vectors.classifers
: Model architectures for classifying college majors.test.py
: Evaluation and demo code for all models.train.py
: Training loops for models.helper.py
: Utility methods for loading and preprocessing data
Run the demo()
function in test.py
The web server provides a RESTful API for getting major recommendations:
python api.py
curl --location --request POST 'http://127.0.0.1:5000/recommend' \
--header 'Content-Type: application/json' \
--data-raw '{
"data": "Construction is cool!"
}'
...
[
"Construction Management",
"Architectural Engineering",
"City and Regional Planning"
]
``