Five Reasons to Go to Machine Learning Week, June 19-24 2022 in Vegas
Five Reasons to Go to Machine Learning Week, June 19-24 2022 in Vegas
Five Reasons to Go to Machine Learning Week, June 19-24 2022 in Vegas
In this special episode, rather than the usual conceptual coverage of machine learning, Eric Siegel will pitch you on the machine learning conference series he founded in 2009, the leading cross-vendor, cross-industry event covering the commercial deployment of machine learning and predictive analytics.
Join him in Las Vegas June 19-24 for Machine Learning Week 2022, with seven tracks of sessions covering the commercial deployment of machine learning. Register to attend one or more of MLW’s five co-located conferences: PAW Business, PAW Financial, PAW Industry 4.0, PAW Healthcare, and Deep Learning World.
MLW Vegas 2022: http://www.machinelearningweek.com
Predictive Analytics World for Climate Tech:https://predictiveanalyticsworldclimate.com/
Predictive Analytics World for Industry 4.0 Munich: https://predictiveanalyticsworldindustry40.eu/
Predictive Analytics World for Healthcare Munich: https://predictiveanalyticsworldhealthcare.eu/
Deep Learning World Munich: https://deeplearningworld.de/
The history of these conferences -- from spawning the Target-predicting-pregnancy publicity debacle to getting dinged by the Hollywood action movie star Chuck Norris: https://www.predictiveanalyticsworld.com/machinelearningtimes/a-brief-history-of-paw-on-its-10-year-anniversary/9936/
From The Podcast
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.comJoin Podchaser to...
- Rate podcasts and episodes
- Follow podcasts and creators
- Create podcast and episode lists
- & much more
Episode Tags
Claim and edit this page to your liking.
Unlock more with Podchaser Pro
- Audience Insights
- Contact Information
- Demographics
- Charts
- Sponsor History
- and More!
- Account
- Register
- Log In
- Find Friends
- Resources
- Help Center
- Blog
- API
Podchaser is the ultimate destination for podcast data, search, and discovery. Learn More
- © 2024 Podchaser, Inc.
- Privacy Policy
- Terms of Service
- Contact Us