{"name":"The Dr. Data Show with Eric Siegel and Luba Gloukhova","short_name":"The Dr. Data Show with Eric Siegel and Luba Gloukhova","theme_color":"#ffffff","start_url":"/","display":"standalone","background_color":"#fff","description":"<p>Eric Siegel and Luba Gloukhova cover why machine learning is the most important, most potent, and most misunderstood technology. And did we mention most important?<br /><br />Yup, it’s the most important – yet most new ML projects fail to deliver value. This podcast will help you:<br /><br />- Make sure machine learning is effective and valuable<br /><br />- Catch common machine learning oversights<br /><br />- Understand ethical pitfalls – concretely<br /><br />- Sniff out all the ”artificial intelligence” malarky<br /><br />This 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.<br /><br />To get machine learning to work, both the tech and business sides must make an effort to reach across wide chasm.<br /><br />About the host:<br /><br />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, 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.<br /><br />https://www.machinelearningweek.com<br /><br />http://www.bizML.com<br /><br />http://www.machinelearning.courses<br /><br />http://www.thepredictionbook.com</p>","icons":[{"src":"https://deow9bq0xqvbj.cloudfront.net/image-logo/13486961/dr_data_3000x3000_-_with_luba_too70mmk_300x300.jpg","sizes":"300x300","type":"image/png"}]}