Book Image

Hands-On Python Deep Learning for the Web

By : Anubhav Singh, Sayak Paul
Book Image

Hands-On Python Deep Learning for the Web

By: Anubhav Singh, Sayak Paul

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)
1
Artificial Intelligence on the Web
3
Using Deep Learning for Web Development
7
Getting Started with Different Deep Learning APIs for Web Development
12
Deep Learning in Production (Intelligent Web Apps)
Appendix: Success Stories and Emerging Areas in Deep Learning on the Web

Using the Cloud Translation API in Python

The Cloud Translation API helps developers to easily integrate language translation functionalities into their applications. It is powered by state-of-the-art neural machine translation, which can be thought of as an amalgamation of deep learning and machine translation. The Cloud Translation API provides programmatic interfaces for using pre-trained models and building production-ready custom models.

Many developers use the Cloud Translation API's pre-trained models to dynamically translate a given set of text into a target language. The Cloud Translate API supports more than 100 languages. But this language library is evolving to empower the developer community. The following screenshot shows a translation of some text written in English to Bengali:

You can always try this on https://cloud.google.com/translate/. But sometimes,...