Book Image

Building Data-Driven Applications with Danfo.js

By : Rising Odegua, Stephen Oni
Book Image

Building Data-Driven Applications with Danfo.js

By: Rising Odegua, Stephen Oni

Overview of this book

Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications. Starting with an overview of modern JavaScript, you’ll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You’ll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you’ll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you’ll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js. By the end of this app development book, you’ll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.
Table of Contents (18 chapters)
1
Section 1: The Basics
3
Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook
10
Section 3: Building Data-Driven Applications

Chapter 10: Introduction to TensorFlow.js

In the previous chapter, you were introduced to the basics of machine learning (ML), and you learned some theoretical foundations that are required in order to build and use ML models.

In this chapter, we'll introduce you to an efficient and popular ML library in JavaScript called TensorFlow.js. By the end of this chapter, you'll know how to install and use TensorFlow.js, how to create tensors, how to operate on tensors using the Core application programming interface (API), as well as how to build a regression model using TensorFlow.js's Layer API.

In this chapter, we will cover the following topics:

  • What is TensorFlow.js?
  • Installing and using TensorFlow.js
  • Tensors and basic operations on tensors
  • Building a simple regression model with TensorFlow.js