• Complain

Tyler Richards - Getting Started with Streamlit for Data Science

Here you can read online Tyler Richards - Getting Started with Streamlit for Data Science full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2021, publisher: Packt Publishing Pvt. Ltd., genre: Home and family. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:

Romance novel Science fiction Adventure Detective Science History Home and family Prose Art Politics Computer Non-fiction Religion Business Children Humor

Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.

Tyler Richards Getting Started with Streamlit for Data Science
  • Book:
    Getting Started with Streamlit for Data Science
  • Author:
  • Publisher:
    Packt Publishing Pvt. Ltd.
  • Genre:
  • Year:
    2021
  • Rating:
    4 / 5
  • Favourites:
    Add to favourites
  • Your mark:
    • 80
    • 1
    • 2
    • 3
    • 4
    • 5

Getting Started with Streamlit for Data Science: summary, description and annotation

We offer to read an annotation, description, summary or preface (depends on what the author of the book "Getting Started with Streamlit for Data Science" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.

Tyler Richards: author's other books


Who wrote Getting Started with Streamlit for Data Science? Find out the surname, the name of the author of the book and a list of all author's works by series.

Getting Started with Streamlit for Data Science — read online for free the complete book (whole text) full work

Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Getting Started with Streamlit for Data Science" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.

Light

Font size:

Reset

Interval:

Bookmark:

Make
Getting Started with Streamlit for Data Science Create and deploy Streamlit web - photo 1
Getting Started with Streamlit for Data Science

Create and deploy Streamlit web applications from scratch in Python

Tyler Richards

BIRMINGHAMMUMBAI Getting Started with Streamlit for Data Science Copyright 2021 - photo 2

BIRMINGHAMMUMBAI

Getting Started with Streamlit for Data Science

Copyright 2021 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Group Product Manager: Kunal Parikh

Publishing Product Manager: Reshma Raman

Senior Editor: Mohammed Yusuf Imaratwale

Content Development Editor: Sean Lobo

Technical Editor: Devanshi Deepak Ayare

Copy Editor: Safis Editing

Project Coordinator: Aparna Ravikumar Nair

Proofreader: Safis Editing

Indexer: Rekha Nair

Production Designer: Vijay Kamble

First published: August 2021

Production reference: 1150721

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80056-550-0

www.packt.com

Contributors
About the author

Tyler Richards is a data scientist at Facebook, working on community integrity. Before this gig, his focus was on helping bolster the state of US elections for the nonprofit Protect Democracy. He is a data scientist and industrial engineer by training, which he gets to make use of in fun ways such as applying machine learning to local campus elections, creating algorithms to help P&G target Tide Pod users, and finding ways to determine the best ping pong players in friend groups. He is always looking for a new project, a new adventure.

About the reviewers

Randy Zwitch is head of developer relations at Streamlit. The developer relations team at Streamlit works with community members from around the world to help develop data apps and democratize decision-making across the enterprise. Randy is also a prolific open source contributor in the Python, Julia, and R communities. In his free time, Randy is an amateur luthier, building electric guitars and other stringed instruments at http://zwitchguitars.com/.

Weston Willingham studied industrial and systems engineering at the University of Florida before pivoting to data science. While completing the Galvanize Data Science Immersive program, Weston built several projects including a neural network for image detection and an audio transcriber trained to his own voice to improve presentation captioning. When not reading books, Weston can be found playing jazz piano and saxophone.

Table of Contents
Preface

Data scientists and machine learning engineers throughout the 2010s have primarily produced static analyses. We create documents to inform decisions, filled with plots and metrics about our findings, or about the models we create. Creating complete web applications that allow users to interact with analyses is cumbersome, to say the least! Enter Streamlit, a Python library for creating web applications built with data folks in mind at every step.

Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes in Python in hours instead of days.

This book takes a hands-on approach to help 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 this 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 and work-related data-focused web applications, and will learn about more complicated topics such as using Streamlit Components, beautifying your apps, and the quick deployment of your new apps.

Next page
Light

Font size:

Reset

Interval:

Bookmark:

Make

Similar books «Getting Started with Streamlit for Data Science»

Look at similar books to Getting Started with Streamlit for Data Science. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.


Reviews about «Getting Started with Streamlit for Data Science»

Discussion, reviews of the book Getting Started with Streamlit for Data Science and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.