Streamlit is an open-source app framework for Machine Learning and Data Science teams.
Streamlit lets you turn data scripts into shareable web apps in minutes. It’s all Python, open-source, and free! And once you’ve created an app you can use our cloud platform to deploy, manage, and share your app!
In this course we will cover everything you need to know concerning streamlit such as
Installing Anaconda and create a virtual env Installing Streamlit , pytube, firebase Setting up GitHub account if you already don’t have one Display Information with StreamlitWidgets with Streamlit Working with data frames ( Loading , Displaying )Creating a image filter ( we use popular Instagram filters) Creating a YouTube video downloader (using pytube api)pytube is a lightweight, dependency-free Python library which is used for downloading videos from the webCreating Interactive plots User selected input value for chart Animated Plot Introduction to Multipage Apps Structuring multipage appsRun a multipage appAdding pagesAdding Authentication to your Streamlit app using Streamlit-AuthenticatorAuthentication via Pickle File Authentication via Database Build a Word Cloud AppBuild a OCR – Image to text conversion with tesseract Build a World Cloud App ChatGPT + Streamlit Build a auto review response generator with chatGPT and Open AI Build a Leetcode problem solver with chatGPT and Open AI Content in progress to be uploaded soon Creating a personal portfolio page with streamlit Deploy Application with Streamlit Cloud Concept of Sessions NTLK with streamlit Working with SQLiteConnecting to database Reading data from database Writing Data into database Additional Apps Static Code quality analyzer No SQL Job Board with Firebase APIConverting random forest model into streamlit application
