ML 013: Recommender Systems with Frank Kane

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.ioAudible.comCacheFly Panel Charles Max WoodGant LabordeDaniel SvobodaBeril Sirmacek Guest Frank Kane Links https://gabriellecrumley.com/ Picks Daniel Svoboda: Silicon Valleymachinelearningmastery.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.comUntil the End of Time: Mind, Matter, and Our Search for Meaning in an Evolving Universe Follow Adventures in Machine Learning on Twitter > @podcast_mlAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.