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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

Product type Paperback

Published in Mar 2019

Publisher

ISBN-13 9781789959413

Length 420 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Science

Authors (3):

Tommy Blanchard

Debasish Behera

Pranshu Bhatnagar

View More author details

Table of Contents (12) Chapters

Data Science for Marketing Analytics

Preface

1. Data Preparation and Cleaning FREE CHAPTER

2. Data Exploration and Visualization

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

Chapter 1. Data Preparation and Cleaning

Note

Learning Objectives

By the end of this chapter, you will be able to:

Create pandas DataFrames in Python
Read and write data into different file formats
Slice, aggregate, filter, and apply functions (built-in and custom) to DataFrames
Join DataFrames, handle missing values, and combine different data sources

Note

This chapter covers basic data preparation and manipulation techniques in Python, which is the foundation of data science.

You have been reading a chapter from

Data Science for Marketing Analytics

Published in: Mar 2019

Publisher:

ISBN-13: 9781789959413

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Authors (3)

Blanchard

Blanchard

Tommy Blanchard earned his PhD from the University of Rochester and did his postdoctoral training at Harvard. Now, he leads the data science team at Fresenius Medical Care North America. His team performs advanced analytics and creates predictive models to solve a wide variety of problems across the company.

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Behera

Behera

Debasish Behera works as a data scientist for a large Japanese corporate bank, where he applies machine learning/AI to solve complex problems. He has worked on multiple use cases involving AML, predictive analytics, customer segmentation, chat bots, and natural language processing. He currently lives in Singapore and holds a Master's in Business Analytics (MITB) from the Singapore Management University.

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Pranshu Bhatnagar

Pranshu Bhatnagar

Pranshu Bhatnagar works as a data scientist in the telematics, insurance, and mobile software space. He has previously worked as a quantitative analyst in the FinTech industry and often writes about algorithms, time series analysis in Python, and similar topics. He graduated with honors from the Chennai Mathematical Institute with a degree in Mathematics and Computer Science and has completed certification courses in Machine Learning and Artificial Intelligence from the International Institute of Information Technology, Hyderabad. He is based in Bangalore, India.

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