In this episode of the SuperDataScience Podcast, I chat with Data Scientist, Peyman Hesami. You will find out what reinforcement learning is and how it works on an intuitive level. You will hear about the differences between reinforcement learning versus classification, or other supervised learning methods, and how it's used for personalization specifically. You will learn about six distinct advantages of reinforcement learning, what role reinforcement learning is going to play in the future of machine learning and why. Also, you will find out how and why Peyman made a career transition to work for a startup, how he's using reinforcement learning, and what is the biggest mistake he has made with reinforcement learning.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/293

The Super Data Science Podcast: Big Data | Analytics Careers | Mentors | Success

SDS 293: True Personalization Through Reinforcement Learning

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As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

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SDS 293: True Personalization Through Reinforcement Learning

Super Data Science: ML & AI Podcast with Jon Krohn