WEB APP DEVELOPMENT AND REAL-TIME WEB ANALYTICS WITH PYTHON : develop and integrate machine... learning algorithms into web apps

Learn to develop and deploy dashboards as web apps using the Python programming language, and how to integrate algorithms into web apps. Author Tshepo Chris Nokeri begins by introducing you to the basics of constructing and styling static and interactive charts and tables before exploring the basics of HTML, CSS, and Bootstrap, including an approach to building web pages with HTML. From there, he’ll show you the key Python web frameworks and techniques for building web apps with them. You’ll then see how to style web apps and incorporate themes, including interactive charts and tables to build dashboards, followed by a walkthrough of creating URL routes and securing web apps. You’ll then progress to more advanced topics, like building machine learning algorithms and integrating them into a web app. The book concludes with a demonstration of how to deploy web apps in prevalent cloud platforms. Web App Development and Real-Time Web Analytics with Python is ideal for intermediate data scientists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have the knowledge necessary to create added value for your organization, as you will understand how to link front-end and back-end development, including machine learning. What You Will Learn Create interactive graphs and render static graphs into interactive ones Understand the essentials of HTML, CSS, and Bootstrap Gain insight into the key Python web frameworks, and how to develop web applications using them Develop machine learning algorithms and integrate them into web apps Secure web apps and deploy them to cloud platforms Who This Book Is For Intermediate data scientists, machine learning engineers, and web developers. Table of Contents About the Author About the Technical Reviewer Acknowledgments Chapter 1: Tabulating Data and Constructing Static 2D and 3D Charts Tabulating the Data 2D Charting Box-Whisker Plot Histogram Line Plot Scatter Plot Density Plot Violin Plot Regression Plot Joint Plot Heatmap 3D Charting Conclusion Chapter 2: Interactive Tabulation and Charting Plotly Tabulating the Data with Plotly Interactive Charting 2D Charting Box Plot Violin Plot Histogram 2D Histogram Distribution Plot Scatter Plot Scatter Matrix Density Plot Bar Chart Pie Chart Sunburst Choropleth Map Heatmap 3D Charting Indicators Conclusion Chapter 3: Containing Functionality and Styling for Interactive Charts Updating Graph Layout Updating Plotly Axes Including Range Slider Including Buttons to a Graph Subplots Styling Charts Altering Color Schemes Color Sequencing Customizing Traces Conclusion Chapter 4: Essentials of HTML Communication Between a Web Browser and a Web Server URL Structure Domain Hosting Shared Web Hosting Managed Web Hosting Web Servers HyperText Markup Language HTML Elements Headings Paragraphs Div Span Buttons Text Box Input File Upload Label Form Meta Tag Practical Example Viewing Web Page Source Conclusion Chapter 5: Python Web Frameworks and Apps Web Frameworks Web Apps Flask WSGI Werkzeug Jinja Installing Flask Initializing a Flask Web App Flask App Code Deploy a Flask Web App Dash Installing Dash Dependencies Initializing a Dash Web App Dash Web App Code Deploy a Dash Web App Jupyter Dash Conclusion Chapter 6: Dash Bootstrap Components Number Input Text Area Select Radio Items Checklist Switches Tabs Button Table Conclusion Chapter 7: Styling and Theming a Web App Styling Cascade Styling Sheet Bootstrap Dash Bootstrapping Dash Core Components Dash Bootstrap Components Implementing Dash Bootstrap Components Theming Dash HTML Components Dash Web Application Layout Design Responsive Grid System Conclusion Chapter 8: Building a Real-Time Web App Dash App Structure Importing Key Dependencies Loading an External CSS File Loading the Bootstrap Icons Library Initializing a Web App Navigation Bars Top Navigation Bar Alerts and Notifications Messages Profile Navigation Bar with a Toggle Button Specifying the Responsive Side Navigation Bar Specifying the Web App CSS Code Side Navigation Bar Menus and Submenus Search Functionality Creating Interactive Charts Containing an Interactive Table and Allowing Generating a Report and Enabling Download Specifying the App Layout Specifying a Callback Function Callback for a Responsive Side Navigation Bar Callback for URL Routing Specifying a Callback Function for Unhiding Content Specifying a Callback Function for Interactive Charts Specifying a Callback Function for Unhiding an Interactive Table Specifying a Callback Function for an Interactive Table Specifying a Callback Function for Callback for Data Download Run the Dash App Conclusion Chapter 9: Basic Web App Authentication Authentication with Dash Auth Authentication with Flask Login Form Login on Home Page Conclusion Chapter 10: Dash into a Full Website Home Page Footer Navigation Bar Banner Callback to Collapse the Navigation for Small Screens Home Page Contact Us Billing/Checkout Conclusion Chapter 11: Integrating a Machine Learning Algorithm into a Web App An Introduction to Linear Regression An Introduction to sklearn Preprocessing Splitting Data into Training and Test Data Standardization Training an Algorithm Predictions Integrating an Algorithm to a Web App Initializing a Web App Navigation Bars Search Functionality Containing Interactive Tables for Results Specifying the App Layout and Callbacks for Responsive Side Menus and URL Routing Specifying a Callback to Load Independent Variables Values Specifying a Callback for Loading the Dependent Variable Values Specifying a Callback for Descriptive Statistics Specifying a Callback for Correlation Analysis Results Specifying a Callback for an Algorithm’s Predictions Specifying a Callback for an Algorithm’s Intercept and Coefficients Specifying a Callback for an Algorithm’s Evaluation Results Running the Dash App Conclusions Chapter 12: Deploying a Web App on the Cloud Integrated Development Environment PyCharm Virtual Environment File Structure Integrating Innumerable Python Files Hosting Web Apps Dash Enterprise Heroku Conclusion Index Learn to develop and deploy dashboards as web apps using the Python programming language, and how to integrate algorithms into web apps. Author Tshepo Chris Nokeri begins by introducing you to the basics of constructing and styling static and interactive charts and tables before exploring the basics of HTML, CSS, and Bootstrap, including an approach to building web pages with HTML. From there, he’ll show you the key Python web frameworks and techniques for building web apps with them. You’ll then see how to style web apps and incorporate themes, including interactive charts and tables to build dashboards, followed by a walkthrough of creating URL routes and securing web apps. You’ll then progress to more advanced topics, like building machine learning algorithms and integrating them into a web app. The book concludes with a demonstration of how to deploy web apps in prevalent cloud platforms. __Web App Development and Real-Time Web Analytics with Python__ is ideal for intermediate data scientists, machine learning engineers, and web developers, who have little or no knowledge about building web apps that implement bootstrap technologies. After completing this book, you will have the knowledge necessary to create added value for your organization, as you will understand how to link front-end and back-end development, including machine learning. **What You Will Learn** * Create interactive graphs and render static graphs into interactive ones * Understand the essentials of HTML, CSS, and Bootstrap * Gain insight into the key Python web frameworks, and how to develop web applications using them Develop machine learning algorithms and integrate them into web apps * Secure web apps and deploy them to cloud platforms Intermediate data scientists, machine learning engineers, and web developers.