In this section, we will take a brief look at some products/companies that used AI at their core to boost their business growth. It's worth noting here that it is not important that your entire product or service is based on any AI technique or algorithm; only having AI in a small portion of it or for a specific feature is enough to boost your product's usefulness and hence the widespread usage of your product by customers. Sometimes, you may not even have AI present in any of the product's features, and instead, you might only use it to perform data analysis and come up with expected trends to make sure your product conforms to the upcoming trends. Let's take a look at what worked for these companies as they made it large.
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