@article{1453622,
      note = {Includes index.},
      author = {Raghavendra, Sujay,},
      url = {http://library.usi.edu/record/1453622},
      title = {Beginner's guide to Streamlit with Python : build  web-based data and machine learning applications /},
      abstract = {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.},
      doi = {https://doi.org/10.1007/978-1-4842-8983-9},
      recid = {1453622},
      pages = {1 online resource (215 pages) :},
}