The talk title is quite provocative but the material discussed not so much. It is true that core data science is iterative, needs to reproducible and more recently explainable. Can you do everything in GUI? It really depends on where you see it from. Early data scientists were programmers before so they loved to code and built tooling around it. While code is still dominant we also see the rise of UI-centric tools - these allow you to build ML pipelines by snapping blocks together. I feel are chasing a "different" type of data scientist. The term data scientist itself has become quite broad.
Code, CLI gives data scientists infinite flexibility but setup, management etc. is a challenge. GUI provides very less flexibility but you will have output fast - works for simpler problems IMHO.
GUI or not data science has to move to cloud-based tools. Whether you write code in browser or CLI on local machine is matter of choice.
Code, CLI gives data scientists infinite flexibility but setup, management etc. is a challenge. GUI provides very less flexibility but you will have output fast - works for simpler problems IMHO.
GUI or not data science has to move to cloud-based tools. Whether you write code in browser or CLI on local machine is matter of choice.