As a Data Scientist, you might want to create dashboards for data visualization, visualize data and even implement business applications to assist stakeholders in making actionable decisions.
Multiple tools and technology can be used to perform those tasks, whether open-source or proprietary software. However, these might not be ideal for the following reasons:
- Some of the open-source technologies require a steep learning curve and hiring individuals with the appropriate expertise. Consequently, organizations may face an increased onboarding time for new employees, higher training costs, and potential challenges in finding qualified candidates.
- Other open-source solutions are great for prototypes but will not scale to a production-ready application
- Similarly, proprietary tools also come with their own challenges, including higher licensing costs, limited customization, and difficulty for businesses to switch to other solutions.
Wouldn’t it be nice if there was a tool that is not only open-source but also easy to learn and able to scale into a full application?
That’s where Taipy comes in handy 🎉
This article will explain what Taipy is, along with some business cases that it can solve before exploring its key features. Furthermore, it will illustrate all the steps to create a full web application.
It is an open-source, 100% Python library and only requires basic knowledge of Python programming. It allows data scientists and machine learning engineers, and any other Python programmer to quickly turn their data and machine learning models into a fully functional web application.
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