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Data Science for Marketing Analytics
Data Science for Marketing Analytics

Data Science for Marketing Analytics: A practical guide to forming a killer marketing strategy through data analysis with Python , Second Edition

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Profile Icon Mirza Rahim Baig Profile Icon Gururajan Govindan Profile Icon Vishwesh Ravi Shrimali
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$29.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (203 Ratings)
eBook Sep 2021 636 pages 2nd Edition
eBook
$29.99
Paperback
$38.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Mirza Rahim Baig Profile Icon Gururajan Govindan Profile Icon Vishwesh Ravi Shrimali
Arrow right icon
$29.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (203 Ratings)
eBook Sep 2021 636 pages 2nd Edition
eBook
$29.99
Paperback
$38.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$29.99
Paperback
$38.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Use data analytics and machine learning in a sales and marketing context
  • Gain insights from data to make better business decisions
  • Build your experience and confidence with realistic hands-on practice

Description

Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making.

Who is this book for?

This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.

What you will learn

  • Load, clean, and explore sales and marketing data using pandas
  • Form and test hypotheses using real data sets and analytics tools
  • Visualize patterns in customer behavior using Matplotlib
  • Use advanced machine learning models like random forest and SVM
  • Use various unsupervised learning algorithms for customer segmentation
  • Use supervised learning techniques for sales prediction
  • Evaluate and compare different models to get the best outcomes
  • Optimize models with hyperparameter tuning and SMOTE

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 07, 2021
Length: 636 pages
Edition : 2nd
Language : English
ISBN-13 : 9781800563889
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Product Details

Publication date : Sep 07, 2021
Length: 636 pages
Edition : 2nd
Language : English
ISBN-13 : 9781800563889
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3
(203 Ratings)
5 star 57.6%
4 star 24.6%
3 star 12.8%
2 star 3.4%
1 star 1.5%
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Robert Fink Nov 01, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The authors do a good job walking the reader through the process of applying data science methods within the marketing analytics space. Throughout your journey, the authors make clever use of practical examples to help illustrate the points while providing the reader an opportunity to practice these new skills. I recommend the book to anyone who is interesting in learning more about the methods and how they are applied.
Amazon Verified review Amazon
Michael Floyd Dec 12, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a great book for Data Science beginners. What you have is the composition of materials so that the answers to your questions are now in one book.
Amazon Verified review Amazon
Lisa Feb 08, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
It is a very good book for beginner. The start kit is very through and it was very useful if you are a first time python user. The explanation is very clear and thorough. There are actual examples as well. The steps to walk through a project or a program is very well thought. It is a very nice book to have if you are trying to get into analysis using Jupyter. For people who have slightly more experience may also well benefited from the root cause analysis through process.
Amazon Verified review Amazon
ankit Oct 31, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Honestly this book is for those who want to start from scratch. The books start from pandas data analysis and goes to talk about regression methods. It talks about different regression methods and the parameters to be compared.The book also has detailed clustering methods with good number of examples and datsets with well explained python codes. Many examples on segmentation problems in campaign analysis are well covered .In the end books talks about comparing different supervised models and parameters to be used with good explanation of fine tuning methods.This is a must read book. I recommend it to all the people who want to learn from scratch to advance levels covering step by step.
Amazon Verified review Amazon
nolan Dec 23, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
First of all, this book is over 600 pages and covers a lot of data science and machine learning topics. It teaches you from entry level to some of the advanced topics in data science. The examples are written in Python but you don’t have to be an expert to understand it. What I liked most about it is that the exercises are real world data science problems and solutions are very well explained for a beginner to understand. The only downside is it doesn’t mention anything about XGBoost or LightGBM which are commonly use in the field. Overall, this book is great introduction to marketing analysis.
Amazon Verified review Amazon
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