Developing and Deploying Applications with Streamlit

[mitsumi]

Published 09/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 27 lectures (2h 8m) | Size: 704.8 MB

The fastest way to build and share data apps.

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 )
Implement a Linear regression Using the Scikit-Learn
Using Streamlit convert linear regression model into a web app
Implement Random Forest Using the Scikit-Learn
Using Streamlit convert Random Forest into a web app
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
Introduction to Multipage Apps
Structuring multipage apps
Run a multipage app
Adding pages
Creating a No-SQL Web app (community job board) using firebase
Creating a example dashboard with streamlit
Creating a personal portfolio page with streamlit
Deploy Application with Streamlit
Future Reading and lifetime access to any future streamlit projects added
Who this course is for
Anyone who is interested Python and Machine Learning
If you want to have a free portfolio page

Download link

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