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Machine Learning Solutions

You're reading from   Machine Learning Solutions Expert techniques to tackle complex machine learning problems using Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788390040
Length 566 pages
Edition 1st Edition
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Table of Contents (19) Chapters Close

Machine Learning Solutions
Foreword
Contributors
Preface
1. Credit Risk Modeling 2. Stock Market Price Prediction FREE CHAPTER 3. Customer Analytics 4. Recommendation Systems for E-Commerce 5. Sentiment Analysis 6. Job Recommendation Engine 7. Text Summarization 8. Developing Chatbots 9. Building a Real-Time Object Recognition App 10. Face Recognition and Face Emotion Recognition 11. Building Gaming Bot List of Cheat Sheets Strategy for Wining Hackathons Index

Building the baseline approach


In this section, we will start implementing the basic model for the customer segmentation application. Furthermore, we will improve this baseline approach. While implementing, we will cover the necessary concepts, technical aspects, and significance of performing that particular step. You can find the code for the customer-segmentation application at this GitHub link: https://github.com/jalajthanaki/Customer_segmentation

The code related to this chapter is given in a single iPython notebook. You can access the notebook using this GitHub link: https://github.com/jalajthanaki/Customer_segmentation/blob/master/Cust_segmentation_online_retail.ipynb.

Refer to the code given on GitHub because it will help you understand things better. Now let's begin the implementation!

Implementing the baseline approach

In order to implement the customer segmentation model, our implementation will have the following steps:

  1. Data preparation

  2. Exploratory data analysis (EDA)

  3. Generating...

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