Developing and Deploying Applications with Streamlit

Name: Developing and Deploying Applications with Streamlit
Price: 59.99 USD
Rating: 3.7 (58 reviews)

The fastest way to build and share data apps.

(58 ratings)

17,671 students

Created by Avinash A

Last updated 2/2023

English

English [Auto]

What you'll 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

Requirements

Basic knowledge of Python programing language
Willingness to learn or know SciKit Learn
Basic knowledge of HTML CSS
Willingness to learn or have prior knowledge of GitHub

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

Who this course is for:

Anyone who is interested Python and Machine Learning
If you want to have a free portfolio page

Avinash A

Software Engineer & Educator

4.1 Instructor Rating
653 Reviews
77,181 Students
6 Courses

I'm a Software Engineer with 10+ years of industry experience in software platform development. I have worked on wide array of technologies among them PHP, Azure , HPC , Databases and Python is where my core strength lies.

Colleagues know me as a team player, technically sound individual who can always be trusted to come up with a out of the box solution. It has been my firm belief that the organizations interest comes first, and I never try to impose my ideas on others. Instead, I spend a considerable of time understanding the business and the audience before suggesting solutions.

The desire to start a course on udemy to share with people the issues I faced with Software so I can help cut the red tape for projects and help increase productivity