Get to look at amazing Streamlit WebApps
Streamlit is a Python library that allows developers to create interactive web-based applications for data visualization and analysis. It is easy to use and allows for the creation of highly interactive and responsive apps with little to no web development experience. The apps created with Streamlit can be shared and deployed easily, making it a useful tool for data scientists, analysts, and researchers to share their work with others. It also allow to build complex machine learning model and share them with other people in an easy way. In this section,I built some WebApps with the streamlit library that allows us to carry out machine learning and basic analysis automatically
A machine learning classifier is a model that is trained to predict the class or category of an input. Streamlit allows developers to easily create interactive web-based applications that incorporate machine learning classifiers. With streamlit, I was able to load, train, and test machine learning classifiers, as well as to display outputs. It also allows for the integration of various widgets and interactive elements, such as sliders and drop-down menus, to allow users to change the parameters of the classifier and see the results in real-time in a user-friendly format.
Converting an Excel file into a Streamlit web app involves using the Streamlit library to create an interactive web interface for the data in the Excel file. One way to do this is to use the pandas library to read the data from the Excel file and then use Streamlit to create visualizations and widgets for interacting with the data.I converted an Excel file into a Streamlit web app which can allow users to easily interact and explore the data. View the project in the link below.