Developing and Deploying Applications with Streamlit

Developing and Deploying Applications with Streamlit, available at $59.99, has an average rating of 3.9, with 44 lectures, 4 quizzes, based on 58 reviews, and has 17671 subscribers.

You will learn about Streamlit and its usefulness. Streamlits features that help up build web , data and machine learning application Deploying streamlit applications on streamlit cloud Personal Portfolio page hosted on streamlit cloud This course is ideal for individuals who are Anyone who is interested Python and Machine Learning or If you want to have a free portfolio page It is particularly useful for Anyone who is interested Python and Machine Learning or If you want to have a free portfolio page.

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Summary

Title: Developing and Deploying Applications with Streamlit

Price: $59.99

Average Rating: 3.9

Number of Lectures: 44

Number of Quizzes: 4

Number of Published Lectures: 44

Number of Published Quizzes: 4

Number of Curriculum Items: 48

Number of Published Curriculum Objects: 48

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Streamlit and its usefulness.

Streamlits features that help up build web , data and machine learning application

Deploying streamlit applications on streamlit cloud

Personal Portfolio page hosted on streamlit cloud

Who Should Attend

Anyone who is interested Python and Machine Learning

If you want to have a free portfolio page

Target Audiences

Anyone who is interested Python and Machine Learning

If you want to have a free portfolio page

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

1. Installing Anaconda and create a virtual env

2. Installing Streamlit , pytube, firebase

3. Setting up GitHub account if you already don’t have one

4. Display Information with Streamlit

5. Widgets with Streamlit 

6. Working with data frames ( Loading , Displaying )

7. Creating a image filter ( we use popular Instagram filters)

8. 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

9. Creating Interactive plots

   1. User selected input value for chart

   2. Animated Plot

10. Introduction to Multipage Apps

    1. Structuring multipage apps

    2. Run a multipage app

    3. Adding pages

11. Adding Authentication to your  Streamlit app using Streamlit-Authenticator

    1. Authentication via Pickle File

    2. Authentication via  Database

12. Build a Word Cloud App

13. Build a OCR – Image to text conversion with tesseract

14. Build a World Cloud App

15. 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 

16. 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

Course Curriculum

Chapter 1: Introduction

Lecture 1: Setting up Anaconda and GitHub

Lecture 2: Creative a virtual env in anaconda

Lecture 3: Test Streamlit is working

Chapter 2: Streamlit Library

Lecture 1: Display text information with streamlit

Lecture 2: Display Data with streamlit

Lecture 3: Display charts with streamlit

Lecture 4: Display media and code with streamlit

Lecture 5: Display chart using external libraries with streamlit

Chapter 3: Interactive widgets with streamlit

Lecture 1: Buttons

Lecture 2: Check Boxes

Lecture 3: Single Item selection

Lecture 4: Multi Item Selection

Lecture 5: Input widgets – Single and multi line text

Lecture 6: Input Widgets- number input

Lecture 7: Uploading file

Lecture 8: Download file

Chapter 4: Streamlit Layout

Lecture 1: Side Bar, Forms, Columns and Expander

Chapter 5: Mutate Data

Lecture 1: Mutate Tabular and Chart Data

Chapter 6: Instagram Filter

Lecture 1: Instagram filters application demo

Lecture 2: Coding Input Layout and accepting image from user

Lecture 3: Converting Input image to Sketch

Lecture 4: Adding Instagram Filters Brannan and Mayfair

Lecture 5: Add Image Download Link

Chapter 7: Build a YouTube Video downloader with pytube Api

Lecture 1: Demo of YouTube Video Downloader we will be building

Lecture 2: Coding and testing a YouTube Video downloader

Chapter 8: Animate your charts with streamlit

Lecture 1: GDP per capita chart animation

Chapter 9: Open API chatGPT with Streamlit

Lecture 1: Creating ChatGPT Account Creation

Lecture 2: ChatGPT Example Search Queries

Lecture 3: Creating Virtual env for chatgpt

Lecture 4: Building auto reponse generator any customer review

Lecture 5: ChatGPT Leetcode solutions Idea

Lecture 6: ChatGPT Leetcode problem solver integration with Streamlit

Lecture 7: ChatGPT Leetcode problem solver integration with Streamlit with language select

Chapter 10: Multipage Streamlit Apps

Lecture 1: Converting GDP per capita into 3 pages basic_data , basic_plot and animated_plot

Chapter 11: Adding Authentication to your Streamlit app using Streamlit-Authenticator

Lecture 1: Adding Authentication to Pytube app using Streamlit-Authenticator (pickle File)

Chapter 12: Build a Word Cloud App

Lecture 1: Demo of Word Cloud App

Lecture 2: Installing Libraries for Word Cloud App

Lecture 3: Lets Build the word Cloud App

Chapter 13: Image to text Conversion App – OCR

Lecture 1: Demo of OCR App we are building

Lecture 2: Installing tesseract library

Lecture 3: Coding the OCR App

Chapter 14: Digital portfolio

Lecture 1: Digital Portfolio using Streamlit Demo

Chapter 15: When you should use Streamlit?

Lecture 1: Flash or Dash or Streamlit ?

Chapter 16: Bonus Lecture

Lecture 1: Bonus Lecture

Instructors

Avinash A
Software Engineer & Educator

Rating Distribution

1 stars: 5 votes

2 stars: 3 votes

3 stars: 3 votes

4 stars: 15 votes

5 stars: 32 votes

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