What is this?
- Clust is clustering (in customer segmentation) platform. Started from thesis assigment.
- At the moment, clust using k-medoids and gap statistic to provide customer segment with model RFMD showing all labeling possibility and next action.
- Documentation : Google Docs
How this project is organize?
- core: py notebook, csv, cleaning
- repository: database
- services: fetching from external api
- routes: controller
- storage: all images, files
- dataset: example data for clustering
- test: just testing code
How is this project routing ?
- routes --> usecases(optional) --> services/repository/core
Clustering step
- Step 1 = rawdata router - import and visualization
- Step 2 = modeling router - rfmd table, gap statistic, visualization
- Step 3 = clustering router - clustering, visualization
- Step 4 = detail router - showing table.
How to run this project?
- Make sure python3 is installed
- Import the databases from 'database/sunrise.dump'
- Set connection port in '.env'
- Run command below
- python -m venv
- \Scripts\activate
- pip install -r requirements.txt
- python -m uvicorn main:app --reload (for next, just run this code)
Tricks?
- if using global, not env and want to run without script "python -m"
- ** in windows, add to path C:\Users%Username%\AppData\Roaming\Python\Python311\Scripts\ for using uvicorn main:app --reload
- pip freeze > requirements.txt (saving installed library)
Credit: anantaw81 (PLEASE DO NOT COPY THIS PROJECT WITHOUT PERMISSION)