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Four Things the Machine Learning Industry Must Learn from Self-Driving Cars

Four Things the Machine Learning Industry Must Learn from Self-Driving Cars

Released Monday, 21st March 2022
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Four Things the Machine Learning Industry Must Learn from Self-Driving Cars

Four Things the Machine Learning Industry Must Learn from Self-Driving Cars

Four Things the Machine Learning Industry Must Learn from Self-Driving Cars

Four Things the Machine Learning Industry Must Learn from Self-Driving Cars

Monday, 21st March 2022
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When it comes to deploying machine learning, we must learn from the self-driving car movement – both to gain inspiration as to what it takes and as a major cautionary tale as to what mistakes to avoid. This episode covers four things the entire machine learning industry must learn from the self-driving car movement.

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The Dr. Data Show with Eric Siegel

Eric Siegel covers why machine learning is the most important, most potent, and most misunderstood technology. And did I mention most important?Yup, it’s the most important – yet most new ML projects fail to deliver value. This podcast will help you:- Make sure machine learning is effective and valuable- Catch common machine learning oversights- Understand ethical pitfalls – concretely- Sniff out all the ”artificial intelligence” malarkyThis podcast is for both data scientists and business leaders of all kinds – such as executives, directors, line of business managers, and consultants – who are involved in or affected by the deployment of machine learning.To get machine learning to work, both the tech and business sides must make an effort to reach across wide chasm.About the host: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 Applications Summit, 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,” which has been used in courses at hundreds of universities, 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 the graduate *computer science* courses in ML and AI. Later, he served as a *business school* professor at UVA Darden. Eric has appeared on numerous media channels, including Bloomberg, National Geographic, and NPR, and has published in Newsweek, HBR, SciAm blog, WaPo, WSJ, and more.https://www.machinelearningweek.comhttp://www.bizML.comhttp://www.machinelearning.courseshttp://www.thepredictionbook.com

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