Hands-On Python Deep Learning for the Web: Integrating neural network architectures to build smart web apps with Flask,Django,and TensorFlow
by: Anubhav Singh and Sayak Paul
Print Length 页数: 404 pages
Publisher finelybook 出版社: Packt Publishing (15 May 2020)
Language 语言: English
ISBN-10: 1789956080
ISBN-13: 9781789956085
Book Description
By finelybook
Use the power of deep learning with Python to build and deploy intelligent web applications
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.
What you will learn
Explore deep learning models and implement them in your browser
Design a smart web-based client using Django and Flask
Work with different Python-based APIs for performing deep learning tasks
Implement popular neural network models with TensorFlow.js
Design and build deep web services on the cloud using deep learning
Get familiar with the standard workflow of taking deep learning models into production
Table of Contents
Section 1: Artificial Intelligence on the Web
Chapter 1: Demystifying Artificial Intelligence and Fundamentals of
Machine Learning
Section 2: Using Deep Learning for Web Development
Chapter 2: Getting Started with Deep Learning Using Python
Chapter 3: Creating Your First Deep Learning Web Application
Chapter 4: Getting Started with TensorFlow. js
Section 3: Getting Started with Different Deep Learning APIs for
Web Development
Chapter 5: Deep Learning through APls
Chapter 6: Deep Learning on Google Cloud Platform Using Python
Chapter 7: DL on AWS Using Python: Object Detection and Home
Automation
Chapter 8: Deep Learning on Microsoft Azure Using Python
Section 4: Deep Learning in Production(Intelligent Web Apps)
Chapter 9: A General Production Framework for Deep
Learning-Enabled Websites
Chapter 10: Securing Web Apps with Deep Learning
Chapter 11: DIY-A Web DL Production Environment
Chapter 12: Creating an E2E Web App Using DL APIs and Customer
Support Chatbot
Appendix: Success Stories and Emerging Areas in Deep Learning on
the Web
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Index
