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Building Data-Driven Applications with Danfo.js

You're reading from   Building Data-Driven Applications with Danfo.js A practical guide to data analysis and machine learning using JavaScript

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781801070850
Length 476 pages
Edition 1st Edition
Languages
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Authors (2):
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Stephen Oni Stephen Oni
Author Profile Icon Stephen Oni
Stephen Oni
Rising Odegua Rising Odegua
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Rising Odegua
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Table of Contents (18) Chapters Close

Preface 1. Section 1: The Basics
2. Chapter 1: An Overview of Modern JavaScript FREE CHAPTER 3. Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook
4. Chapter 2: Dnotebook - An Interactive Computing Environment for JavaScript 5. Chapter 3: Getting Started with Danfo.js 6. Chapter 4: Data Analysis, Wrangling, and Transformation 7. Chapter 5: Data Visualization with Plotly.js 8. Chapter 6: Data Visualization with Danfo.js 9. Chapter 7: Data Aggregation and Group Operations 10. Section 3: Building Data-Driven Applications
11. Chapter 8: Creating a No-Code Data Analysis/Handling System 12. Chapter 9: Basics of Machine Learning 13. Chapter 10: Introduction to TensorFlow.js 14. Chapter 11: Building a Recommendation System with Danfo.js and TensorFlow.js 15. Chapter 12: Building a Twitter Analysis Dashboard 16. Chapter 13: Appendix: Essential JavaScript Concepts 17. Other Books You May Enjoy

Installing and using TensorFlow.js

As we mentioned earlier, TensorFlow.js can be installed and run in both the browser and Node.js environment. In the following paragraphs, we'll show you how to achieve this, starting off with the browser.

Setting up TensorFlow.js in the browser

There are two ways of installing TensorFlow.js in the browser. These are outlined here:

  • Via script tags
  • Using package managers such as Node Package Manager (npm) or Yarn

Installing via script tags

Installing TensorFlow.js via a script tag is easy. Just place the script tag in the header file of your HyperText Markup Language (HTML) file, as shown in the following code snippet:

<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@3.6.0/dist/tf.min.js"></script>

To confirm that TensorFlow.js is installed, open the HTML file in the browser, and check the network tabs. You should see the name tf.min.js and a status code of 200, as shown in the following...

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