Data mining and visualization are important skills to have in the modern era, regardless of your job responsibilities. In order to make it easier to learn and use these techniques and technologies Blaž Zupan and Janez Demšar, along with many others, have created Orange. In this episode they explain how they built a visual programming interface for creating data analysis and machine learning workflows to simplify the work of gaining insights from the myriad data sources that are available. They discuss the history of the project, how it is built, the challenges that they have faced, and how they plan on growing and improving it in the future.
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- Your host as usual is Tobias Macey and today I’m interviewing Blaž Zupan and Janez Demsar about Orange, a toolbox for interactive machine learning and data visualization in Python
- How did you get introduced to Python?
- What is Orange and what was your motivation for building it?
- Who is the target audience for this project?
- How is the graphical interface implemented and what kinds of workflows can be implemented with the visual components?
- What are some of the most notable or interesting widgets that are available in the catalog?
- What are the limitations of the graphical interface and what options do user have when they reach those limits?
- What have been some of the most challenging aspects of building and maintaining Orange?
- What are some of the most common difficulties that you have seen when users are just getting started with data analysis and machine learning, and how does Orange help overcome those gaps in understanding?
- What are some of the most interesting or innovative uses of Orange that you are aware of?
- What are some of the projects or technologies that you consider to be your competition?
- Under what circumstances would you advise against using Orange?
- What are some widgets that you would like to see in future versions?
- What do you have planned for future releases of Orange?
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- University of Ljubljani
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