In this final chapter of this book, we have tried to inspire you to build your next deep learning project and use it on a web platform. You might be interested in the stories of more such companies that transformed their businesses using AI and ruled the market space. If you take a look at almost every website you visit, they will all use elements of AI and deep learning on them in some way, be it in the form of recommendation systems or advertisements (which are again promotional recommendation systems). We then covered the upcoming topics in the field of deep learning, which are looking for implementation on websites in the very near future. It would be amazing if you could come up with a service based on any of these topics!
Hands-On Python Deep Learning for the Web
By :
Hands-On Python Deep Learning for the Web
By:
Overview of this book
When used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you'll cover the latest tools and technological practices that are being used to implement deep learning in web development using Python.
Starting with the fundamentals of machine learning, you'll focus on DL and the basics of neural networks, including common variants such as convolutional neural networks (CNNs). You'll learn how to integrate them into websites with the frontends of different standard web tech stacks. The book then helps you gain practical experience of developing a deep learning-enabled web app using Python libraries such as Django and Flask by creating RESTful APIs for custom models. Later, you'll explore how to set up a cloud environment for deep learning-based web deployments on Google Cloud and Amazon Web Services (AWS). Next, you'll learn how to use Microsoft's intelligent Emotion API, which can detect a person's emotions through a picture of their face. You'll also get to grips with deploying real-world websites, in addition to learning how to secure websites using reCAPTCHA and Cloudflare. Finally, you'll use NLP to integrate a voice UX through Dialogflow on your web pages.
By the end of this book, you'll have learned how to deploy intelligent web apps and websites with the help of effective tools and practices.
Table of Contents (19 chapters)
Preface
Artificial Intelligence on the Web
Free Chapter
Demystifying Artificial Intelligence and Fundamentals of Machine Learning
Using Deep Learning for Web Development
Getting Started with Deep Learning Using Python
Creating Your First Deep Learning Web Application
Getting Started with TensorFlow.js
Getting Started with Different Deep Learning APIs for Web Development
Deep Learning through APIs
Deep Learning on Google Cloud Platform Using Python
DL on AWS Using Python: Object Detection and Home Automation
Deep Learning on Microsoft Azure Using Python
Deep Learning in Production (Intelligent Web Apps)
A General Production Framework for Deep Learning-Enabled Websites
Securing Web Apps with Deep Learning
DIY - A Web DL Production Environment
Creating an E2E Web App Using DL APIs and Customer Support Chatbot
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Appendix: Success Stories and Emerging Areas in Deep Learning on the Web
Customer Reviews