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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

Setting up a deep-learning-based cloud environment

Before we begin setting up a cloud-based deep learning environment, we might wonder why would we need it or how a cloud-based deep learning environment would benefit us. Deep learning requires a massive amount of mathematical calculation. At every layer of the neural network, there is a mathematical matrix undergoing multiplication with another or several other such matrices. Furthermore, every data point itself can be a vector instead of a singular entity. Now, to train over several repetitions, such a deep learning model would require a lot of time just because of the number of mathematical operations involved.

A GPU-enabled machine would be much more efficient at executing these operations because a GPU is made specifically for high-speed mathematical calculations however, GPU-enabled machines are costly and may not be affordable...

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