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Hands-on Machine Learning with JavaScript

You're reading from   Hands-on Machine Learning with JavaScript Solve complex computational web problems using machine learning

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788998246
Length 356 pages
Edition 1st Edition
Languages
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Author (1):
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Burak Kanber Burak Kanber
Author Profile Icon Burak Kanber
Burak Kanber
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Table of Contents (18) Chapters Close

Title Page
Packt Upsell
Contributors
Preface
1. Exploring the Potential of JavaScript 2. Data Exploration FREE CHAPTER 3. Tour of Machine Learning Algorithms 4. Grouping with Clustering Algorithms 5. Classification Algorithms 6. Association Rule Algorithms 7. Forecasting with Regression Algorithms 8. Artificial Neural Network Algorithms 9. Deep Neural Networks 10. Natural Language Processing in Practice 11. Using Machine Learning in Real-Time Applications 12. Choosing the Best Algorithm for Your Application 1. Other Books You May Enjoy Index

Chapter 12. Choosing the Best Algorithm for Your Application

There are three distinct phases in the software-engineering process: conception, implementation, and deployment. This book has primarily focused on the implementation phase of the process, which is when a software engineer develops the core functionality (that is, a machine learning (ML) algorithm) and features of the project. In the last chapter, we discussed matters concerning the deployment phase. Our learning is nearly complete.

In this final chapter, we'll turn to the conception phase in order to round out our understanding of the full ML development process. Specifically, we'll discuss how to choose the best algorithm for a given problem. The ML ecosystem is evolving, intimidating, and full of jargon unfamiliar even to experienced software developers. I often see students of ML get stuck at the beginning of the process, not knowing where to start in a vast and unfamiliar landscape. What they don't know yet is that once you...

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