Developing and Deploying Applications with Streamlit

The fastest way to build and share data apps.

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 Streamlit
Widgets 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 web
Creating Interactive plots
User selected input value for chart
Animated Plot
Introduction to Multipage Apps
Structuring multipage apps
Run a multipage app
Adding pages
Adding Authentication to your  Streamlit app using Streamlit-Authenticator
Authentication via Pickle File
Authentication via  Database
Build a Word Cloud App
Build 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 SQLite
Connecting to database
Reading data from database
Writing Data  into database
Additional Apps
Static Code quality analyzer
No SQL Job Board with Firebase  API
Converting random forest model into streamlit application