Adventures in Machine Learning

ML 013: Recommender Systems with Frank Kane


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In this episode of Adventures in Machine Learning, the amazing author and course creator Frank Kane entertains our panel with information and examples. Beril Sirmacek, Gant Laborde, Daniel Svoboda, & Charles Wood talk with Frank Kane about recommender systems. The discussion elaborates on collaborative and content based recommendation systems, how they all work and how amazing they can be. Frank’s variety of experience provides fun stories, exciting examples, and a roadmap for beginners filled the complex domain with friendly stories. This episode is a MUST LISTEN for people interested in getting into Machine Learning or recommender systems. Sponsors
  • Machine Learning for Software Engineers by Educative.io
  • Audible.com
  • CacheFly
Panel
  • Charles Max Wood
  • Gant Laborde
  • Daniel Svoboda
  • Beril Sirmacek
Guest
  • Frank Kane
Links
  • https://gabriellecrumley.com/
Picks Daniel Svoboda:
  • Silicon Valley
  • machinelearningmastery.com
Beril Sirmacek:
  • XAI course 2020 ~ Module2 ~ Introduction to AI & ML
Gant Laborde:
  • https://mlconf.eu/
Charles Max Wood:
  • Stroopwafel (dutch food)
  • https://www.podcastgrowthsummit.co/
Frank Kane:
  • https://sundog-education.com/
  • datascience.com
  • Until the End of Time: Mind, Matter, and Our Search for Meaning in an Evolving Universe
Follow Adventures in Machine Learning on Twitter > @podcast_ml

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Adventures in Machine LearningBy Charles M Wood

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