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Data Science for Marketing Analytics

You're reading from   Data Science for Marketing Analytics Achieve your marketing goals with the data analytics power of Python

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Product type Paperback
Published in Mar 2019
Publisher
ISBN-13 9781789959413
Length 420 pages
Edition 1st Edition
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Authors (3):
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Tommy Blanchard Tommy Blanchard
Author Profile Icon Tommy Blanchard
Tommy Blanchard
Debasish Behera Debasish Behera
Author Profile Icon Debasish Behera
Debasish Behera
Pranshu Bhatnagar Pranshu Bhatnagar
Author Profile Icon Pranshu Bhatnagar
Pranshu Bhatnagar
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Table of Contents (12) Chapters Close

Data Science for Marketing Analytics
Preface
1. Data Preparation and Cleaning 2. Data Exploration and Visualization FREE CHAPTER 3. Unsupervised Learning: Customer Segmentation 4. Choosing the Best Segmentation Approach 5. Predicting Customer Revenue Using Linear Regression 6. Other Regression Techniques and Tools for Evaluation 7. Supervised Learning: Predicting Customer Churn 8. Fine-Tuning Classification Algorithms 9. Modeling Customer Choice Appendix

Summary


In this chapter, we have explored the way data is processed and have figured out intuitive details about it. We can now perform advanced analysis and create visualizations to make processing easy to understand. We can use the knowledge that we have gained to solve further problems, explore hidden relationships, and do further analysis easily. Let's look at some applications of this with problems we can solve in the next chapter.

You have been reading a chapter from
Data Science for Marketing Analytics
Published in: Mar 2019
Publisher:
ISBN-13: 9781789959413
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