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Web App Development Made Simple with Streamlit

Web App Development Made Simple with Streamlit

By : Moscato
4.3 (10)
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Web App Development Made Simple with Streamlit

Web App Development Made Simple with Streamlit

4.3 (10)
By: Moscato

Overview of this book

This book is a comprehensive guide to the Streamlit open-source Python library and simplifying the process of creating web applications. Through hands-on guidance and realistic examples, you’ll progress from crafting simple to sophisticated web applications from scratch. This book covers everything from understanding Streamlit's central principles, modules, basic features, and widgets to advanced skills such as dealing with databases, hashes, sessions, and multipages. Starting with fundamental concepts like operation systems virtualization, IDEs, development environments, widgets, scripting, and the anatomy of web apps, the initial chapters set the groundwork. You’ll then apply this knowledge to develop some real web apps, gradually advancing to more complex apps, incorporating features like natural language processing (NLP), computer vision, dashboards with interactive charts, file uploading, and much more. The book concludes by delving into the implementation of advanced skills and deployment techniques. By the end of this book, you’ll have transformed into a proficient developer, equipped with advanced skills for handling databases, implementing secure login processes, managing session states, creating multipage applications, and seamlessly deploying them on the cloud.
Table of Contents (23 chapters)
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1
Part 1: Getting Started with Streamlit
5
Part 2: Building a Basic Web App for Essential Streamlit Skills
10
Part 3: Developing Advanced Skills with a Covid-19 Detection Tool
15
Part 4: Advanced Techniques for Secure and Customizable Web Applications

Implementing NLP Techniques for Text Analysis and Processing in Streamlit

Translation and sentiment analysis are very important techniques used in natural language processing (NLP) for analyzing and processing text data.

Translation is the process of converting text from one language to another. Sentiment analysis is the process of identifying the emotional tone or sentiment of a piece of text. It is used to analyze customer feedback, social media sentiment, and product reviews.

Both of them are powerful techniques that enable NLP applications to process and analyze text data and extract valuable insights from it. In this chapter, we will continue our exploration of web app creation with Streamlit while learning more about the techniques. In the previous chapter, we completed the Text Analysis voice of our web application’s menu, and now, finally, we are ready to finish all the parts of this application.

By the end of the chapter, our first web application will be more...

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