You're reading from Hands-On Python Deep Learning for the Web

Product typeBook

Published inMay 2020

Reading LevelBeginner

PublisherPackt

ISBN-139781789956085

Edition1st Edition

Languages

Python

Tools

Django TensorFlow

Concepts

Deep Learning

Authors (2):

Anubhav Singh

Sayak Paul

View More author details

Your first deep learning web application with TF.js

In this section, we are going to develop a web application with the help of TF.js. This application will include the steps for a standard, full stack, deep learning-enabled web project. We will begin by preparing the data, we will then study the project architecture briefly, and then, we will proceed toward building the required components as we go.

Preparing the dataset

The Iris flower dataset, in its original form, is a CSV file containing the data of 150 rows split into 5 columns in a comma-separated format, with each entry separated by a new line.

However, we will be using a JSON format of the data for easier operability with JavaScript. The dataset in JSON format can...

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Hands-On Python Deep Learning for the Web

Published in: May 2020Publisher: PacktISBN-13: 9781789956085

Authors (2)

Anubhav Singh

Anubhav Singh, a web developer since before Bootstrap was launched, is an explorer of technologies, often pulling off crazy combinations of uncommon tech. An international rank holder in the Cyber Olympiad, he started off by developing his own social network and search engine as his first projects at the age of 15, which stood among the top 500 websites of India during their operational years. He's continuously developing software for the community in domains with roads less walked on. You can often catch him guiding students on how to approach ML or the web, or both together. He's also the founder of The Code Foundation, an AI-focused start-up. Anubhav is a Venkat Panchapakesan Memorial Scholarship awardee and an Intel Software Innovator.
Read more about Anubhav Singh

Sayak Paul

Sayak Paul is currently with PyImageSearch, where he applies deep learning to solve real-world problems in computer vision and bring solutions to edge devices. He is responsible for providing Q&A support to PyImageSearch readers. His areas of interest include computer vision, generative modeling, and more. Previously at DataCamp, Sayak developed projects and practice pools. Prior to DataCamp, Sayak worked at TCS Research and Innovation (TRDDC) on data privacy. There, he was a part of TCS's critically acclaimed GDPR solution called Crystal Ball. Outside of work, Sayak loves to write technical articles and speak at developer meetups and conferences.
Read more about Sayak Paul

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