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Hands-On Python Deep Learning for the Web

You're reading from   Hands-On Python Deep Learning for the Web Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow

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Product type Paperback
Published in May 2020
Publisher Packt
ISBN-13 9781789956085
Length 404 pages
Edition 1st Edition
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Authors (2):
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Sayak Paul Sayak Paul
Author Profile Icon Sayak Paul
Sayak Paul
Anubhav Singh Anubhav Singh
Author Profile Icon Anubhav Singh
Anubhav Singh
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Toc

Table of Contents (19) Chapters Close

Preface Artificial Intelligence on the Web
Demystifying Artificial Intelligence and Fundamentals of Machine Learning FREE CHAPTER 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 Other Books You May Enjoy Appendix: Success Stories and Emerging Areas in Deep Learning on the Web

Creating a Dialogflow bot with the personality of a customer support representative

Dialogflow is a very popular tool used to create chatbots. Similar to Wit.ai, Botpress, Microsoft Bot Framework, and several other ready-to-deploy services available for creating chatbots, Dialogflow comes with the added advantage of its tight integration with Google Cloud Platform (GCP) and the possibility of using Dialogflow agents as actions for the Google Assistant, which runs natively on billions of Android devices.

Dialogflow was formerly known as Api.ai. After its acquisition by Google, it was renamed and has since grown in its popularity and extensibility. The platform allows very easy integration with several platforms, such as Facebook Messenger, Telegram, Slack, Line, Viber, and several other major communication platforms.

The project we will develop in this chapter will follow the following...

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