This is all the information relating to my final project "A Look at Cataloguing Artworks". This project fit the requirements necessary for Wei Tang's "CS412: Introduction to Machine Learning" at the University of Illinois at Chicago. (This was the Fall 2021 Semester course.) The work looks to answers questions on MoMA's public collection.
The final project had three components: a written report, presentation, and code.
- The documents folder contains the presentation and written report. In there, I go in detail on what my observations were, the questions that I asked surrounding the data, and any pitfalls which were presented.
- The code folder contains a Python file (extension .py), a Jupyter Notebook file (extension .ipynb), and tables (extension .csv). The Python file has limited code inside, as I quickly switched to Jupyter Notebook for my data exploration and research. I leave it just as a testament to the beginning of my research. The tables are created on demand within the Jupyter Notebook file.
- The collection folder redirects to Muesum of Modern Art's (MoMA) repository. This was used to obtain the data for the research.