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R Machine Learning By Example

R Machine Learning By Example

By : Raghav Bali
4.6 (14)
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R Machine Learning By Example

R Machine Learning By Example

4.6 (14)
By: Raghav Bali

Overview of this book

Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems. This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems. You’ll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms. Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.
Table of Contents (10 chapters)
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9
Index

Market basket analysis

Market basket analysis consists of some modeling techniques which are typically used by retailers and e-commerce marketplaces to analyze shopping carts and transactions to find out what customers buy the most, what kind of items they buy, what the peak season is for specific items to be sold the most, and so on. We will be focusing on item based transactional patterns in this chapter for detecting and predicting what items people are buying and are most likely to buy. Let us first look at the formal definition of market basket analysis and then we will look at core concepts, metrics, and techniques tied to it. Finally, we will conclude with how to actually use these results to make data driven decisions.

What does market basket analysis actually mean?

Market basket analysis typically encompasses several modeling techniques based upon the simple principle that while shopping if you buy a certain group of items (also known as an itemset in machine learning lingo), you...

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