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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

Preface

Deep learning techniques can be used to develop intelligent web apps. Over the last few years, tremendous growth in the number of companies adopting deep learning techniques in their products and businesses has been observed. There has been a significant surge in the number of start-ups providing AI and deep learning-based solutions for niche problems. This book introduces numerous tools and technological practices used to implement deep learning in web development using Python.

To start with, you will learn about the fundamentals of machine learning, with a focus on deep learning and the basics of neural networks, along with their common variants, such as convolutional neural networks, and how you can integrate them into websites with frontends built with different standard web tech stacks. You will create your deep learning-enabled web application using Python libraries such as Django and Flask by creating REST APIs for custom models. You will set up a cloud environment for deep learning-based web deployments on Google Cloud and AWS, and get guidance on how to use their battle-tested deep learning APIs. Further, you will use Microsoft's Intelligent Emotion API, which can detect human emotions from a picture of a face. You will also get to grips with deploying real-world websites, and you will get great insights into securing those websites using reCaptcha and Cloudflare for a robust experience. Finally, you will use natural language processing to recommend restaurants from user reviews and to integrate a voice UX on your web pages through Dialogflow.

By the end of this book, you'll be able to deploy your intelligent web apps and websites with the help of the best tools and practices.

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