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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

Exploring Jupyter Notebooks

While working on a project relating to deep learning, you must deal with a huge amount of variables of various types and arrays of various dimensions. Also, since the data contained in them is massive and keeps changing after nearly every step, we need a tool that helps us to observe the output produced by each step so that we can proceed accordingly. A Jupyter Notebook is one such tool. Jupyter Notebooks are known for their simplicity, and their wide support of features and platforms are currently the standard tool for developing deep-learning solutions. The reasons for their popularity can be understood by considering the fact that several of the top tech giants offer their own version of the tool, such as Google Colaboratory and Microsoft Azure Notebooks. Moreover, the popular code-hosting website GitHub has been providing a native rendering of Jupyter...

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