“Even if you don't drink one bit of the A.I. Kool-Aid and you're a senior expert practitioner in machine learning, when you're trying to start a new initiative at your corporation, you're still very liable to make this extremely prevalent mistake that leads to a lack of deployment. And the mistake is that we all, on some level, are fetishizing the technology.”-      Eric Siegel

 

In this episode of Data Chats, Chris Richardson interviews Eric Siegel, Ph.D., leading consultant and former Columbia University professor who makes machine learning understandable and captivating. He is also the founder of the Predictive Analytics World and Deep Learning World conference series, which has served more than 17,000 attendees since 2009.They discuss:

How to use A.I. to improve your organization’s capabilities and performance

Common mistakes business leaders make with understanding machine learning

Why top data scientists fail to make successful models most of the time

How operational changes lead to improved data analysis

What separates a great organization from the rest when it comes to predictive analytics

Necessity of socialization and buy-in to successfully implement predictive analysis 

Ethical implications and risks of machine learning

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