Skip to content

The group project for the Computer Science course at the University of St. Gallen.

Notifications You must be signed in to change notification settings

LisaKathi/CS-Project

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

42 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CS-Project

The group project for the Computer Science course at the University of St. Gallen. Our final product can be found in myappfinal.py

Overview of the Notebooks / Python files & Dataframes:

  1. Original Dataset Source: https://data.mendeley.com/datasets/2nfvz8g27c/1
  • AppraiSet_complete_dataset.csv: the complete original dataset used for our data cleaning.
  • AppraiSet_testing_dataset.csv: the orginial testing dataset, not actively used -> we wanted to clean the data ourselves to better fit our project needs
  • AppraiSet_training_dataset.csv: the original training dataset, not actively used -> we wanted to clean the data ourselves to better fit our project needs
  1. Data Clearning and the Machine Learning Model
  • 1_Notebook.ipynb: majority of the data cleaning including material category
  • artist_name.ipynb: final data cleaning including arist_rank and the development of our ML model
  • Artiste_name(streamlitteam).py: integration of the machine learning model into streamlit
  • cleaned.csv: Our cleaned dataset used in final project
  • cleaned_tow.csv: Our cleaned dataset + column title of work
  1. First Attemps at Streamlit
  • myapp.py : first attempt at making a streamlit app, not used in final project
  • test_björn.py: testing streamlit functions, not used in final project
  • test_lorenzo.py: testing streamlit functions, not used in final project
  • fiona_update.py: improving sliders and filters with streamlit
  1. API Inclusion
  • StreamlitAPI_combined.py : not used in final project, first attempt at the integration of the two apis (artsy and google)
  • 2 api.py : combined google api and artsy api, artsy to search for artist info and google for image search
  • artsy_google_api.py : final version of the two apis, used in final project
  1. Creating a Final Product
  • Streamlit_DataDiscovery_Prediction_combined.py: First attempt at combining prediction and data discovery with ML model, and combined API
  • myappfinal.py: Our final streamlit product, including the Prediction, Data Discovery, API usage and Visualization pages plus the final design

About

The group project for the Computer Science course at the University of St. Gallen.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published