Everand Logo

Welcome to Everand!

  • Discover this podcast and so much more

    Podcasts are free to enjoy without a subscription. We also offer ebooks, audiobooks, and so much more for just $11.99/month.

    029: Dive Into Deep Learning and Find Out Where Machines Can Outperform Humans With Ben Taylor

    029: Dive Into Deep Learning and Find Out Where Machines Can Outperform Humans With Ben Taylor

    FromSuper Data Science: ML & AI Podcast with Jon Krohn

    Start listeningView podcast show

    029: Dive Into Deep Learning and Find Out Where Machines Can Outperform Humans With Ben Taylor

    FromSuper Data Science: ML & AI Podcast with Jon Krohn

    ratings:
    Length:
    66 minutes
    Released:
    Feb 23, 2017
    Format:
    Podcast episode

    Description

    In this episode of the SuperDataScience Podcast, I chat with Chief Data Scientist Ben Taylor. You will learn about the role of AI in recruitment, know about a crash course in deep learning and discuss on where machines can outperform humans.

    If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/29
    Released:
    Feb 23, 2017
    Format:
    Podcast episode

    Titles in the series (100)

    The Super Data Science podcast with Jon Krohn brings you the latest and most important machine learning, artificial intelligence, and broader data-world topics from across both academia and industry. As the quantity of data on our planet doubles every couple of years and this trend is set to continue for decades to come, there's an unprecedented opportunity for you to make an enormous impact in your lifetime. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, and commercialization − everything you need to crush it with data science.