東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Beginner's guide to Streamlit with P...

Raghavendra, Sujay.

FindBook

Google Book

Amazon

博客來

Beginner's guide to Streamlit with Python = build web-based data and machine learning applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Beginner's guide to Streamlit with Python/ by Sujay Raghavendra.
其他題名:	build web-based data and machine learning applications /
作者:	Raghavendra, Sujay.
出版者:	Berkeley, CA :Apress : : 2023.,
面頁冊數:	xxi, 203 p. :ill., digital ;24 cm.
內容註:	1. Introduction to Streamlit -- 2.Table and Chart Elements -- 3.Charts/Visualization -- 4.Data and Media Elements -- 5. Buttons -- 6. Forms -- 7.Navigaations -- 8.Control Flow and Advanced Features -- 9. NLP Project -- 10. Computer Vision Project.
Contained By:	Springer Nature eBook
標題:	Web applications. -
電子資源:	https://doi.org/10.1007/978-1-4842-8983-9
ISBN:	9781484289839

Beginner's guide to Streamlit with Python = build web-based data and machine learning applications /
Raghavendra, Sujay.

Beginner's guide to Streamlit with Pythonbuild web-based data and machine learning applications /[electronic resource] :by Sujay Raghavendra. - Berkeley, CA :Apress :2023. - xxi, 203 p. :ill., digital ;24 cm.

1. Introduction to Streamlit -- 2.Table and Chart Elements -- 3.Charts/Visualization -- 4.Data and Media Elements -- 5. Buttons -- 6. Forms -- 7.Navigaations -- 8.Control Flow and Advanced Features -- 9. NLP Project -- 10. Computer Vision Project.

This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you'll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You'll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you'll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit. After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own. You will: Start developing web applications using Streamlit Understand Streamlit's components Utilize media elements in Streamlit Visualize data using various interactive and dynamic Python libraries Implement models in Streamlit web applications.

ISBN: 9781484289839

Standard No.: 10.1007/978-1-4842-8983-9doiSubjects--Topical Terms:

2072989
Web applications.

LC Class. No.: TK5105.875.I6 / R34 2023

Dewey Class. No.: 006.78

Beginner's guide to Streamlit with Python = build web-based data and machine learning applications /
LDR:02831nmm a2200325 a 4500 001 2315209
003 DE-He213
005 20221216080141.0
006 m d
007 cr nn 008mamaa
008 230902s2023 cau s 0 eng d
020 $a 9781484289839 $q (electronic bk.)
020 $a 9781484289822 $q (paper)
024 7 $a 10.1007/978-1-4842-8983-9 $2 doi
035 $a 978-1-4842-8983-9
040 $a GP $c GP
041 0 $a eng
050 4 $a TK5105.875.I6 $b R34 2023
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.78 $2 23
090 $a TK5105.875.I6 $b R142 2023
100 1 $a Raghavendra, Sujay. $3 3488183
245 1 0 $a Beginner's guide to Streamlit with Python $h [electronic resource] : $b build web-based data and machine learning applications / $c by Sujay Raghavendra.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2023.
300 $a xxi, 203 p. : $b ill., digital ; $c 24 cm.
505 0 $a 1. Introduction to Streamlit -- 2.Table and Chart Elements -- 3.Charts/Visualization -- 4.Data and Media Elements -- 5. Buttons -- 6. Forms -- 7.Navigaations -- 8.Control Flow and Advanced Features -- 9. NLP Project -- 10. Computer Vision Project.
520 $a This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you'll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You'll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you'll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit. After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own. You will: Start developing web applications using Streamlit Understand Streamlit's components Utilize media elements in Streamlit Visualize data using various interactive and dynamic Python libraries Implement models in Streamlit web applications.
650 0 $a Web applications. $3 2072989
650 0 $a Artificial intelligence. $3 516317
650 0 $a Machine learning. $3 533906
650 0 $a Python (Computer program language) $3 729789
650 1 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Python. $3 3201289
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-8983-9
950 $a Professional and Applied Computing (SpringerNature-12059)