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Machine Learning and Generative AI for Marketing

You're reading from   Machine Learning and Generative AI for Marketing Take your data-driven marketing strategies to the next level using Python

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Product type Paperback
Published in Aug 2024
Publisher Packt
ISBN-13 9781835889404
Length 482 pages
Edition 1st Edition
Languages
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Authors (2):
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Nicholas C. Burtch Nicholas C. Burtch
Author Profile Icon Nicholas C. Burtch
Nicholas C. Burtch
Yoon Hyup Hwang Yoon Hyup Hwang
Author Profile Icon Yoon Hyup Hwang
Yoon Hyup Hwang
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Toc

Table of Contents (16) Chapters Close

Preface 1. The Evolution of Marketing in the AI Era and Preparing Your Toolkit FREE CHAPTER 2. Decoding Marketing Performance with KPIs 3. Unveiling the Dynamics of Marketing Success 4. Harnessing Seasonality and Trends for Strategic Planning 5. Enhancing Customer Insight with Sentiment Analysis 6. Leveraging Predictive Analytics and A/B Testing for Customer Engagement 7. Personalized Product Recommendations 8. Segmenting Customers with Machine Learning 9. Creating Compelling Content with Zero-Shot Learning 10. Enhancing Brand Presence with Few-Shot Learning and Transfer Learning 11. Micro-Targeting with Retrieval-Augmented Generation 12. The Future Landscape of AI and ML in Marketing 13. Ethics and Governance in AI-Enabled Marketing 14. Other Books You May Enjoy
15. Index

Who this book is for

This book targets a diverse group of professionals at the intersection of technology and marketing, including:

  • Marketing professionals at any level seeking to leverage AI/ML for data-driven decision-making and enhance their customer engagement strategies
  • Data scientists and analysts in the marketing domain looking to apply advanced AI/ML techniques to solve real-world marketing challenges
  • ML engineers and software developers aiming to build or integrate AI-driven tools and applications for marketing purposes
  • Business leaders and entrepreneurs who must understand the impact of AI on marketing to drive innovation and maintain their competitive advantage in today’s landscape

Each reader is presumed to have a foundational proficiency in Python programming and a basic to intermediate grasp of ML principles and data science methodologies. They are likely already in or aspire to be in roles where the application of AI/ML directly influences marketing outcomes and business strategies.

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