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    Home » Computers & Internet » Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R
    Computers & Internet

    Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R

    TeamBy TeamNovember 10, 2025No Comments3 Mins Read0 Views
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    1762743428 719TiXxn3rL. SL1360 Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R Edu Expertise Hub data science
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    Price: $48.99 - $35.80
    (as of Nov 10, 2025 02:57:09 UTC – Details)

    amazon buy now button 300x148 1 Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R Edu Expertise Hub data science

    Optimize your marketing strategies through analytics and machine learning

    Key Features:

    Understand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitability

    Book Description:

    Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies.

    This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R.

    By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.

    What you will learn:

    Learn how to compute and visualize marketing KPIs in Python and RMaster what drives successful marketing campaigns with data scienceUse machine learning to predict customer engagement and lifetime valueMake product recommendations that customers are most likely to buyLearn how to use A/B testing for better marketing decision makingImplement machine learning to understand different customer segments

    Who this book is for:

    If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples.


    From the brand

    Packt Brand Story - Data SciencePackt Brand Story - Data Science

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    Bestsellers

    Publisher ‏ : ‎ Packt Publishing
    Publication date ‏ : ‎ March 29, 2019
    Language ‏ : ‎ English
    Print length ‏ : ‎ 464 pages
    ISBN-10 ‏ : ‎ 1789346347
    ISBN-13 ‏ : ‎ 978-1789346343
    Item Weight ‏ : ‎ 1.86 pounds
    Dimensions ‏ : ‎ 7.5 x 1.05 x 9.25 inches
    Best Sellers Rank: #1,695,274 in Books (See Top 100 in Books) #372 in Data Modeling & Design (Books) #570 in Artificial Intelligence (Books) #2,361 in Artificial Intelligence & Semantics
    Customer Reviews: 4.1 4.1 out of 5 stars 82 ratings var dpAcrHasRegisteredArcLinkClickAction; P.when(‘A’, ‘ready’).execute(function(A) { if (dpAcrHasRegisteredArcLinkClickAction !== true) { dpAcrHasRegisteredArcLinkClickAction = true; A.declarative( ‘acrLink-click-metrics’, ‘click’, { “allowLinkDefault”: true }, function (event) { if (window.ue) { ue.count(“acrLinkClickCount”, (ue.count(“acrLinkClickCount”) || 0) + 1); } } ); } }); P.when(‘A’, ‘cf’).execute(function(A) { A.declarative(‘acrStarsLink-click-metrics’, ‘click’, { “allowLinkDefault” : true }, function(event){ if(window.ue) { ue.count(“acrStarsLinkWithPopoverClickCount”, (ue.count(“acrStarsLinkWithPopoverClickCount”) || 0) + 1); } }); });

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