[ CourseWikia ] Udemy - Build a Data Science web app using Streamlit torrent

[ CourseWikia.com ] Build a Data Science web app using Streamlit

Download More Courses Visit and Support Us -->> https://CourseWikia.com
New | Created by Leo Bravo | Last updated 2/2021
Duration: 2 hours | 3 sections | 13 lectures | Video: 1280x720, 44 KHz | 1.4 GB
Genre: eLearning | Language: English + Sub
Learn how to convert your data science code into a web app

What you'll learn
Learn how to convert a data science local app into a web app
Learn how to build a web app using Streamlit
Learn how to build a data analysis using Python, Numpy, Pandas, Sklearn and Matplotlib
Learn how to adapt a plain data analysis Python code to a Streamlit code
Learn how to train a linear regression

Requirements
You need to know the basic about Python
You don’t need previous knowledge in data science or machine learning
Description
In this course, you are going to learn how you can build a web app focused on Data Science or Machine Learning projects. To do this, you will use the framework Streamlit, a tool that allows you to easily build a web app.

This is a practical course, in which we will build first a data analysis code to analyze a dataset, then train a model, and finally use the model to do some predictions. Then, we will adapt this code to convert it into a web app using Streamlit. Adapting this code will allow you to learn how you can easily create a web app based on python code.

Use Winrar to Extract. And use a shorter path when extracting, such as C: drive

ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)
Download More Courses Visit and Support Us -->> https://CourseWikia.com

Get More Tutorials and Support Us -->> https://AppWikia.com

We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...