Predictive Analytics by Eric Siegel offers a fascinating introduction to the world of machine learning, detailing how it influences various sectors such as finance, healthcare, and marketing. The book provides numerous case studies and insights into the latest techniques, making it accessible to both lay readers and experts. It covers topics like predicting human behavior, managing risk, and optimizing business strategies.
Eric Siegel's "The AI Playbook" is a comprehensive guide to successfully deploying machine learning in real-world applications. It delves into the practical aspects of implementing AI, moving beyond theoretical concepts to address the challenges of integration and value creation. The book emphasizes the importance of understanding business needs and aligning AI solutions with strategic goals. It provides a structured approach to project planning, execution, and evaluation, offering valuable insights for both technical and business professionals. Ultimately, it aims to empower readers to effectively leverage machine learning to drive tangible business outcomes.
We are in a Generative AI hype cycle. Every executive looking at the potential generative AI today is probably thinking about how they can allocate their department's budget to building some AI use cases. However, many of these use cases won't make it into production.
In a similar vein, the hype around machine learning in the early 2010s led to lots of hype around the technology, but a lot of the value did not pan out. Four years ago, VentureBeat showed that 87% of data science projects did not make it into production. And in a lot of ways, things haven’t gotten much better. And if we don't learn why that is the case, generative AI could be destined to a similar fate.
Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI World, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.
In the episode, Adel and Eric explore the reasons why machine learning projects don't make it into production, the BizML Framework or how to bring business stakeholders into the room when building machine learning use cases, the skill gap between business stakeholders and data practitioners, use cases of organizations have leveraged machine learning for operational improvements, what the previous machine learning hype cycle can teach us about generative AI and a lot more.
Links Mentioned in the Show:
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