![]() ![]() Kaggle allows challenge owners to download all of the submissions with their public and private scores. The first trick is in the data preparation For more motivation to use Bokeh, just check the demo dashboards. ![]() It is easy to embed plots generated from Bokeh to a website, as it can generate HTML pages and it’s also easy to create a bokeh application. ![]() I got to know about the Bokeh python library a few months ago and chose it for this project, as it provides a good platform to create interactive and customizable visualizations. The Bokeh libraryĪmong data visualization tools, there are several options to choose from creating a dashboard. This gave me great motivation to make an interactive dashboard from the leaderboard. As our yearly in-class challenge emerged to be an interesting battle, we were interested in how the number of daily submissions and the dynamics of the leaderboard changed in time. As a co-instructor of a data-science course at Budapest University of Technology and Economics, I’m thrilled to see how my students cope with a machine learning challenge in an in-class Kaggle competition. Kaggle is a platform for data scientists and students to test their algorithms and knowledge to solve various challenges. The dashboard from the Kaggle challenge leaderboard. Follow me, this blog post could be a good reference to anyone interested in creating a similar project and taking advantage of Bokeh’s awesome interactive data visualization tools. In this post, I’ll showcase Bokeh’s fundamental tools with my latest project: a dashboard from a Kaggle challenge leaderboard. Bokeh provides a great deal of interactivity while one can still code in their familiar python environment. If you’re a data enthusiast, as you dive into the world of data visualization tools, you’ll probably encounter python’s Bokeh library. Tips and tricks on how to do an interactive visualization from the epic battle of Kaggle challenge participants ![]()
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