Have you always wanted a flexible & interactive visualization that is easy for others to work with without handling all the Javascript libraries? Or do you want to build a user interface for your Machine Learning Model? This talk has you covered with building data apps in Python using Streamlit with examples of a Travel Visualization App using Google Maps Data & an UI for the ImageNet Model.
In this talk, I showcase couple of different use cases where you can build your data focussed applications using Streamlit, an open source library in pure Python.
In the first use case, I cover how you can build interactive dashboards using different Streamlit components. These dashboards can be easily deployed & the consumers can easily work with the interactive dashboards without worrying about all the dependencies that need to be installed to run the Jupyter notebooks. In the showcase, I will go over how you can build a dashboard of your historical travels using Google Maps Location History including some memories from them from Flickr.
In the second showcase, I will describe how users can create a quick interface for their machine learning model using Streamlit. These interfaces are much faster to develop than building a custom frontend interface for machine learning models with the help of Javascript libraries. In the demo, I showcase how I built an UI for the ImageNet Model.
The showcases will showcase how these data based web apps can be built using Python functions & Streamlit components.
Speakers: Nithish Raghunandanan Matteo Bertucci