Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time.
You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps.
By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.
publication date
2021-08-20
what you will learn
Set up your first development environment and create a basic Streamlit app from scratch
Explore methods for uploading, downloading, and manipulating data in Streamlit apps
Create dynamic visualizations in Streamlit using built-in and imported Python libraries
Discover strategies for creating and deploying machine learning models in Streamlit
Use Streamlit sharing for one-click deployment
Beautify Streamlit apps using themes, Streamlit Components, and Streamlit sidebar
Implement best practices for prototyping your data science work with Streamlit
key features
Learn how to showcase machine learning models in a Streamlit application effectively and efficiently * Become an expert Streamlit creator by getting hands-on with complex application creation * Discover how Streamlit enables you to create and deploy apps effortlessly
approach
Complete with step-by-step explanations of essential concepts, practical examples, and tutorials, you will begin with a basic run-through of Streamlit, and continue learning new applications and features until you reach the edge of Streamlit knowledge, and can whip up web applications on the fly without difficulty.
audience
This book is for data scientists and machine learning enthusiasts who want to create web apps using Streamlit. Whether you’re a junior data scientist looking to deploy your first machine learning project in Python to improve your resume or a senior data scientist who wants to use Streamlit to make convincing and dynamic data analyses, this book will help you get there! Prior knowledge of Python programming will assist with understanding the concepts covered.
short description
Getting Started with Streamlit for Data Science takes you from the basics of web app development in the Streamlit library and machine learning model deployment in Heroku and AWS. The book shows you how you can use Streamlit for a variety of projects to improve job applications and resumes and much more.
subtitle
Create and deploy Streamlit web applications from scratch in Python
keywords
Data Science applications, visualization, interactive apps, Machine Learning, data science books, data science for dummies, data science python, data science projects
Product ISBN
9781800565500
