Streamlit BootCamp
Build beautiful web apps for your Data Science and Machine Learning projects in a fast and easy way using Streamlit.
Lectures -29
Resources -9
Duration -2 hours
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Course Description
ARE YOU LOOKING A FAST AND EASY WAY TO CREATE WEB APPS AND DASHBOARDS FOR YOUR DATA SCIENCE AND MACHINE LEARNING PROJECTS THEN THIS IS THE PERFECT COURSE FOR YOU.
Streamlit is an open-source Python library that makes it easy to create and share beautiful, custom web apps for machine learning and data science that can be used to share analytics results, build complex interactive experiences, and illustrate new machine learning models. In just a few minutes you can build and deploy powerful data apps.
On top of that, developing and deploying Streamlit apps is incredibly fast and flexible, often turning application development time from days into hours.
In this course you will learn:
Different input types in streamlit
Data display elements
Layouts and Containers
How to add images and videos to your Streamlit web app
Different Chart elements like Line Chart, Bar Chart etc...
3 Complete Projects using Machine Learning and Streamlit.
Stock Market Index Prediction App
Calories Burned Calculator App
Insurance Premium Prediction App
At the end of the course, you will have built several applications that you can include in your Data Science and Machine Learning portfolio. You will also have a new skill to add to your resume.
After completing this course you will be able to quickly build web apps and dashboards for your Data Science and Machine Learning Projects using Streamlit.
Goals
- Building complete Web Applications from Scratch using Streamlit.
- Develop Strong Skills about ALL Streamlit's Basic and Advanced Features.
- Use Streamlit to create Data Science and Machine Learning Web Apps.
- Learn to build beautiful User Interface for your ML models using Streamlit.
Prerequisites
- Basic Knowledge of Python Programming Language.
- Basic understanding about Data Science and Machine Learning.
- Basic understanding of Pandas, Numpy and Matplotlib.
![Streamlit BootCamp Streamlit BootCamp](https://d3mxt5v3yxgcsr.cloudfront.net/courses/14157/course_14157_image.jpg)
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
3 Lectures
-
Introduction and Welcome 01:31 01:31
-
Course Overview and Key Learning Outcomes 03:32 03:32
-
Installation and Setuo 01:04 01:04
Text Elements in Streamlit
1 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Data Display Elements in Streamlit
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Chart Elements in Streamlit
4 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Input Widgets in Streamlit
9 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Media Items in Streamlit
2 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Layouts and Containers
3 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Projects
4 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
![Raj Chhabria](https://www.tutorialspoint.com/assets/profiles/588663/profile/200_485343-1692728304.jpg)
Raj Chhabria
My name is Raj Chhabria and I am a Computer Science Engineer with specialization in Data Science. I am an accomplished coder and programmer, and I enjoy using my skills to contribute to student community by my Courses. Here I intend to share my knowledge in most condensed form through my courses.
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