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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
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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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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

Fundamentals of generative AI

Generative AI (GenAI) refers to a subset of AI capable of generating new content, be it text, images, videos, or even synthetic data, that mirrors real-world examples. Unlike traditional AI models, which are designed to interpret, classify, or predict data based on inputs, GenAI takes it a step further by creating new, previously unseen outputs. It does this by understanding and learning from existing data patterns to produce novel outputs that maintain a logical continuity with the input data.

We were introduced to GenAI in Chapter 1, and we further touched upon it and its applications for sentiment analysis in Chapter 5. Before beginning our discussion of pre-trained models and ZSL, we will explore the fundamental technical considerations of GenAI, what it is (and is not), and why it’s so impactful for generating marketing content. While the focus of the hands-on examples in this chapter will involve text generation, important concepts that...

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