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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

To get the most out of this book

To maximize the benefits of this book, it is recommended that you have basic familiarity with Python. However, the book is structured to accommodate a wide range of expertise levels, from beginners to advanced practitioners. Here are a few tips to help you get the most out of this book:

  1. Engage with the code examples: Practical examples are provided throughout the book to illustrate key concepts. Actively engaging with these examples by running the code and experimenting with variations will deepen your understanding and enhance your skills.
  2. Apply the knowledge: Try to apply the techniques and strategies discussed in the book to your own marketing projects. This practical application will help reinforce the concepts and demonstrate their real-world relevance.
  3. Stay updated: The fields of AI and ML are rapidly evolving. Staying up to date with the latest advancements, tools, and best practices through continuous learning and professional development will ensure that you remain at the forefront of this exciting domain.

The line graphs in this book may look slightly different from those generated by the provided code. This is because the graphs have been optimized to ensure clarity and ease of understanding; feel free to play around with visualization to achieve the type of outcome you need!

Download the example code files

The code bundle for the book is hosted on GitHub at https://github.com/PacktPublishing/Machine-Learning-and-Generative-AI-for-Marketing. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://packt.link/gbp/9781835889404.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. For example: “Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system.”

Bold: Indicates a new term, an important word, or words that you see on the screen. For instance, words in menus or dialog boxes appear in the text like this. For example: “Select System info from the Administration panel.”

Important notes or suggestions appear like this.

Tips and tricks appear like this.

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