Developing and Deploying Applications with Streamlit

The fastest way to build and share data apps.

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Developing and Deploying Applications with Streamlit

What You Will Learn!

Streamlit and its usefulness.
Streamlit's features that help up build web , data and machine learning application
Deploying streamlit applications on streamlit cloud
Personal Portfolio page hosted on streamlit cloud

Description

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)
1. pytube is a lightweight, dependency-free Python library which is used for downloading videos from the web
Creating Interactive plots
1. User selected input value for chart
2. Animated Plot
Introduction to Multipage Apps
1. Structuring multipage apps
2. Run a multipage app
3. Adding pages
Adding Authentication to your Streamlit app using Streamlit-Authenticator
1. Authentication via Pickle File
2. Authentication via Database
Build a Word Cloud App
Build a OCR - Image to text conversion with tesseract
Build a World Cloud App
ChatGPT + Streamlit
1. Build a auto review response generator with chatGPT and Open AI
2. Build a Leetcode problem solver with chatGPT and Open AI
Content in progress to be uploaded soon
1. Creating a personal portfolio page with streamlit
2. Deploy Application with Streamlit Cloud
3. Concept of Sessions
4. NTLK with streamlit
5. Working with SQLite
  1. Connecting to database
  2. Reading data from database
  3. Writing Data into database
6. Additional Apps
  1. Static Code quality analyzer
  2. No SQL Job Board with Firebase API
  3. Converting random forest model into streamlit application