How to Build an Interactive Front End for Your Python Data Science Models


From natural language processing to spatial analysis, data science models are becoming more advanced every day. For those models to translate into actionable insights, the data needs to be visualized in an interactive, accessible fashion. That’s where front-end analytics tools like Plotly and Dash come in!

Plotly is a globally known data visualization library used by millions of people worldwide. Built on top of Plotly is Dash, an open-source framework that translates individual graphs or charts into interactive Python data apps. These web-based data apps expand far beyond what is possible with a traditional “dashboard”: they are interactive, customizable, and can incorporate all types of AI/ML libraries like ChatGPT, LangChain, and TensorFlow. Additionally, data scientists can be autonomous and own the development to deployment cycle of these data apps without the need for IT or full-stack knowledge.

Session Outline:

In this workshop, Plotly Solutions Engineer Mingo Sanchez will provide a step-by-step tutorial on how to build an interactive front end for your Python data science models. He will cover the following:
● Introduction to the fundamentals of Plotly graphing libraries
● Overview of Dash basic architecture like layouts and callback functions
● Walkthrough of an interactive AI/ML data app
● Examples of tools to help geospatial data use cases
● Showcase other real-world data applications

Prerequisites: Ideally, participants in the workshop should have experience working with Python and tabular data. A starter code repository will be provided in GitHub for all users to download and modify throughout the workshop.


Mingo is a Senior Sales Engineer at Plotly. After graduating from Bowdoin College with a degree in computer science, he started working with organizations in the master data management and data science spaces. Throughout his career, Mingo has partnered with large financial institutions, life sciences organizations, retail companies, and government agencies to help them better understand their data and more effectively serve their customers. Mingo enjoys building relationships with people to understand their pain points and help them solve their most challenging business and technical problems.

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