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R Machine Learning By Example

You're reading from   R Machine Learning By Example Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784390846
Length 340 pages
Edition 1st Edition
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Author (1):
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Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
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Table of Contents (10) Chapters Close

Preface 1. Getting Started with R and Machine Learning FREE CHAPTER 2. Let's Help Machines Learn 3. Predicting Customer Shopping Trends with Market Basket Analysis 4. Building a Product Recommendation System 5. Credit Risk Detection and Prediction – Descriptive Analytics 6. Credit Risk Detection and Prediction – Predictive Analytics 7. Social Media Analysis – Analyzing Twitter Data 8. Sentiment Analysis of Twitter Data Index

Algorithms in machine learning

So far we have developed an abstract understanding of machine learning. We understand the definition of machine learning which states that a task T can be learned by a computer program utilizing data in the form of experience E when its performance P improves with it. We have also seen how machine learning is different from conventional programming paradigms because of the fact that we do not code each and every step, rather we let the program form an understanding of the problem space and help us solve it. It is rather surprising to see such a program work right in front of us.

All along while we learned about the concept of machine learning, we treated this magical computer program as a mysterious black box which learns and solves the problems for us. Now is the time we unravel its enigma and look under the hood and see these magical algorithms in full glory.

We will begin with some of the most commonly and widely used algorithms in machine learning, looking...

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