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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

Understanding the benefits of pretrained ML models

In this short section, I will try to clarify why using pretrained ML models inside our web applications can be a very good and valuable idea.

ML has rapidly evolved in recent years, offering unprecedented opportunities to enhance web applications with intelligent and predictive features. Streamlit, a popular Python library for creating interactive web applications, has gained immense popularity due to its simplicity and flexibility. When combined with pretrained ML models, Streamlit can empower developers to build web applications that leverage the vast potential of AI.

Pretrained ML models are models that have been trained on large datasets for various tasks, such as image recognition, natural language processing, and more. These models have learned rich data representations and can be fine-tuned for specific applications. Incorporating pretrained models into Streamlit web applications can significantly enhance their capabilities...

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