Description
This talk explores how to create art in the R language while highlighting some similarities between the skills required for creating generative art and those needed to perform data science tasks in R.
Because the field of data science is inherently task-oriented, it is no wonder that most people struggle to see the utility of generative art past the bounds of a casual hobby. This talk will invite the participant to learn about generative art while focusing on ""why"" people should create it and its potential place in data science. This talk is suitable for all disciplines and artistic abilities. Furthermore, this talk will aim to expand the participant's perspective on generative art with the following concepts:
- What is generative art and how can it be created in R or Python
- Justifications for generative art within Data Science
- Examples of programming skills that are transferrable between generative art and pragmatic data science projects
Materials: - Link to the talk repo: https://github.com/Meghansaha/a_case_for_genart - Link to the slides: https://meghansaha.github.io/a_case_for_genart/#/title-slide - Link to the artpack package site: https://meghansaha.github.io/artpack/ - Personal Site: https://thetidytrekker.com/