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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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Toc

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

Chapter 9: Basics of Machine Learning

The machine learning (ML) field is growing bigger every day, with tons of research being done, and various types of smart/intelligent applications being built with ML algorithms. The field is gaining more interest and more people are fascinated to know how it works and how to make use of it.

In this chapter, we will try to get a basic understanding of ML why and how it works, and also see various forms of its application to real-life situations.

In this chapter, we'll look at the following topics to understand the basics of ML:

  • Introduction to machine learning
  • Why machine learning works
  • Machine learning problems/tasks
  • Machine learning in JavaScript
  • Applications of machine learning
  • Resources to understand machine learning in depth
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