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.
Do you want to try out some of the tools and applications that you heard about on Podcast.__init__? Do you have a side project that you want to share with the world? Check out Linode at linode.com/podcastinit or use the code podcastinit2019 and get a $20 credit to try out their fast and reliable Linux virtual servers. They’ve got lightning fast networking and SSD servers with plenty of power and storage to run whatever you want to experiment on.
With GoCD’s comprehensive pipeline modeling, you can model complex workflows for multiple teams with ease. And GoCD’s Value Stream Map lets you track a change from commit to deploy at a glance.
GoCD’s real power is in the visibility it provides over your end-to-end workflow. So you get complete control of and visibility into your deployments, across multiple teams.
Say goodbye to deployment panic and hello to consistent, predictable deliveries.
To learn more about GoCD, visit gocd.org for a free download. Professional Support and enterprise add-ons, including disaster recovery, are available.
- Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
- I would like to thank everyone who supports us on Patreon. Your contributions help to make the show sustainable.
- When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at podastinit.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your awesome app. And now you can deliver your work to your users even faster with the newly upgraded 200 GBit network in all of their datacenters.
- If you’re tired of cobbling together your deployment pipeline then it’s time to try out GoCD, the open source continuous delivery platform built by the people at ThoughtWorks who wrote the book about it. With GoCD you get complete visibility into the life-cycle of your software from one location. To download it now go to podcatinit.com/gocd. Professional support and enterprise plugins are available for added piece of mind.
- Visit the site to subscribe to the show, sign up for the newsletter, and read the show notes. And if you have any questions, comments, or suggestions I would love to hear them. You can reach me on Twitter at @Podcast__init__ or email [email protected])
- To help other people find the show please leave a review on iTunes, or Google Play Music, tell your friends and co-workers, and share it on social media.
- 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?
Keep In Touch
- University of Ljubljani
- Data Explorer
- Silicon Graphics
- Visual Programming
- Linear Regression
- Single Cell Genomics
- Transfer Learning
- Orange Video Tutorials