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R Machine Learning Projects

You're reading from  R Machine Learning Projects

Product type Book
Published in Jan 2019
Publisher Packt
ISBN-13 9781789807943
Pages 334 pages
Edition 1st Edition
Languages
Author (1):
Dr. Sunil Kumar Chinnamgari Dr. Sunil Kumar Chinnamgari
Profile icon Dr. Sunil Kumar Chinnamgari

Table of Contents (12) Chapters

Preface 1. Exploring the Machine Learning Landscape 2. Predicting Employee Attrition Using Ensemble Models 3. Implementing a Jokes Recommendation Engine 4. Sentiment Analysis of Amazon Reviews with NLP 5. Customer Segmentation Using Wholesale Data 6. Image Recognition Using Deep Neural Networks 7. Credit Card Fraud Detection Using Autoencoders 8. Automatic Prose Generation with Recurrent Neural Networks 9. Winning the Casino Slot Machines with Reinforcement Learning 10. The Road Ahead
11. Other Books You May Enjoy

Understanding the wholesale customer dataset and the segmentation problem

The UCI Machine Learning Repository offers the wholesale customer dataset at https://archive.ics.uci.edu/ml/datasets/wholesale+customers. The dataset refers to clients of a wholesale distributor. It includes the annual spending in monetary units (m.u.) on diverse product categories. The goal of these projects is to apply clustering techniques to identify segments that are relevant for certain business activities, such as rolling out a marketing campaign. Before we actually use the clustering algorithms to get clusters, let's first read the data and perform some EDA to understand the data using the following code block:

# setting the working directory to a folder where dataset is located
setwd('/home/sunil/Desktop/chapter5/')
# reading the dataset to cust_data dataframe
cust_data = read.csv...
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