LibCoder

Beginner's Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications

1C Agda Python
Beginner's Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications
Автор: Raghavendra Sujay
Дата выхода: 2023
Издательство: Apress Media, LLC.
Количество страниц: 215
Размер файла: 5,4 МБ
Тип файла: PDF
Добавил: LibCoder
Оглавление
Table of Contents....5 About the Author....12 About the Technical Reviewer....13 Acknowledgments....14 Introduction....15 Chapter 1: Introduction to Streamlit....18 What Is Streamlit?....18 Why Streamlit?....19 Why Streamlit for Data Science and ML Engineers?....19 Features of Streamlit....20 Open Source....20 Platforms....20 Ease of Development....20 Interactive Applications....20 Reduced Time of Development....20 No Core Web Development Knowledge....21 Easy to Learn....21 Model Implementation....21 Compatibility....21 Literate Programming Document....22 Streamlit Cloud....22 Optimize Change....22 Error Notifications....23 Comparing Streamlit to Alternative Frameworks....23 Installing Python....25 Installing Streamlit on Windows....26 Installing Streamlit on Linux....26 Installing Streamlit on macOS....26 Testing the Streamlit Installation....27 Creating Our First App....29 Summary....32 Chapter 2: Text and Table Elements....33 Text Elements....33 Titles....34 Headers....35 Subheaders....36 Captions....37 Plain Text....39 Markdown....40 LaTeX....41 Code....42 Data Elements....45 Dataframes....45 Tables....48 Metrics....50 JSON....52 The write() Function as a Superfunction....54 Magic....58 Summary....61 Chapter 3: Visualization....62 The Importance of Visualization....62 Visualization in Streamlit....62 Purpose of Visualization....63 Streamlit Functions....63 Bar....63 Line....65 Area....66 Map....68 Graphviz....69 Seaborn....71 Count....72 Violin....73 Strip....74 Altair....75 Boxplot....76 Area....77 Heatmap....78 Plotly....80 Pie....80 Donut....82 Scatter....83 Line....85 Bar....86 Bar Horizontal....89 Subplots....90 Summary....92 Chapter 4: Data and Media Elements....94 Images....94 Multiple Images....99 Background Image....102 Resizing an Image....103 Audio....105 Video....107 Balloon....110 Snowflake....111 Emojis....112 Summary....113 Chapter 5: Buttons and Sliders....114 Buttons....114 Radio Buttons....115 Check Boxes....117 Drop-Downs....119 Multiselects....121 Download Buttons....123 Progress Bars....124 Spinners....126 Summary....127 Chapter 6: Forms....128 Text Box....128 Text Area....132 Number Input....133 Time....135 Date....136 Color....138 File Upload....140 Text/Docx Document....141 PDF Upload....146 Dataset Upload....148 Image Upload....150 Uploading Multiple Images....151 Saving Uploaded Documents....153 Submit Button....157 Summary....158 Chapter 7: Columns and Navigation....159 Columns....159 Spaced-Out Columns....160 Columns with Padding....162 Grids....164 Expanders/Accordions....165 Containers....167 Empty Containers....169 Sidebars....170 Multipage Navigation....171 Main Page....172 Pages....172 Summary....174 Chapter 8: Control Flow and Advanced Features....175 Alert Box....175 st.info()....175 st.warning()....176 st.success()....176 st.error()....176 st.exception()....176 Control Flow....177 Stop Execution....178 Rerun the Script....178 st.form_submit_button....179 Advanced Features....180 Configuring the Page....180 st.echo....181 st.experimental_show....182 Session State....183 Performance....185 Caching....185 st.experimental_memo....186 st.experimental_memo.clear()....187 st.experimental_singleton....187 st.experimental_singleton.clear....187 Summary....188 Chapter 9: Natural Language Processing....189 NLP App Creation....189 User Input....190 Cleaning the Text....190 Predictions....191 Setting Up Files....194 Requirement Text....195 setup.sh....195 Procfile....196 GitHub Repository Creation....197 Heroku....197 Deployment....199 Summary....201 Chapter 10: Computer Vision in Streamlit....202 Installing Libraries....202 Model Deployment....203 Upload Image....203 Map Image Classes....204 Apply Imaging Techniques....204 Model Preprocessing....205 Predictions....205 Complete Code....206 Index....209

Описание

В этом материале разберём тему: streamlit.

Streamlit reduces development time for web-based application prototypes of data and machine learning models. This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. As you’ll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models.

Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. 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. You’ll also explore performance optimization techniques necessary for data modules in a Streamlit application. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit. Following this, you’ll see how to deploy Streamlit applications on various platforms.

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.

What You Will LearnHow to start developing web applications using StreamlitWhat are Streamlit's componentsMedia elements in StreamlitHow to visualize data using various interactive and dynamic Python librariesHow to implement models in Streamlit web applicationsWho This Book Is ForProfessionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development.

Если материал оказался полезен — сохраните страницу.

streamlit data machine learning application python build based

Частые вопросы

Можно ли скачать «Beginner's Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications» бесплатно?

Да, «Beginner's Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications» доступна для бесплатного скачивания на нашем сайте в формате PDF. Ссылка на файл находится на этой странице.

В каком формате и какого размера файл?

Книга предоставляется в формате PDF, размер файла 5,4 МБ.

Кто автор и когда вышла книга?

автор — Raghavendra Sujay, издательство Apress Media, LLC., год выпуска 2023, 215 страниц.

О чём книга «Beginner's Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications»?

This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps.

Похожие материалы