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Machine Learning and Generative AI for Marketing

Machine Learning and Generative AI for Marketing

By : Yoon Hyup Hwang, Nicholas C. Burtch
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Machine Learning and Generative AI for Marketing

Machine Learning and Generative AI for Marketing

By: Yoon Hyup Hwang, Nicholas C. Burtch

Overview of this book

In the dynamic world of marketing, the integration of artificial intelligence (AI) and machine learning (ML) is no longer just an advantage—it's a necessity. Moreover, the rise of generative AI (GenAI) helps with the creation of highly personalized, engaging content that resonates with the target audience. This book provides a comprehensive toolkit for harnessing the power of GenAI to craft marketing strategies that not only predict customer behaviors but also captivate and convert, leading to improved cost per acquisition, boosted conversion rates, and increased net sales. Starting with the basics of Python for data analysis and progressing to sophisticated ML and GenAI models, this book is your comprehensive guide to understanding and applying AI to enhance marketing strategies. Through engaging content & hands-on examples, you'll learn how to harness the capabilities of AI to unlock deep insights into customer behaviors, craft personalized marketing messages, and drive significant business growth. Additionally, you'll explore the ethical implications of AI, ensuring that your marketing strategies are not only effective but also responsible and compliant with current standards By the conclusion of this book, you'll be equipped to design, launch, and manage marketing campaigns that are not only successful but also cutting-edge.
Table of Contents (16 chapters)
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Index

Creating Compelling Content with Zero-Shot Learning

Having introduced the promise of large language models in Chapter 5, we will go deeper into related topics in this chapter, extending our analysis from their role in data augmentation and sentiment analysis to their broader impact across different domains. This chapter introduces zero-shot learning (ZSL), a method in machine learning where a model can correctly make predictions for new, unseen classes without having received any specific training examples for those classes. It discusses the potential of ZSL and its application within the area of generative AI to create marketing copy. The discussion highlights how ZSL, an efficient tool to complement traditional marketing content creation processes, can revolutionize the generation of marketing copy.

We will start with an in-depth discussion of the core principles of generative AI and navigate through the capabilities and limitations of these technologies, which will set the...

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