Recommendation engines for learning, with Marc Zao-Sanders - No 54
For this interview I spoke with Marc Zao-Sanders, CEO of Filtered about recommendation engines for learning
Learning While Working Podcast · Sprout Labs
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Show Notes
For this interview I spoke with Marc Zao-Sanders, CEO of Filtered, a platform that makes learning recommendations. In our daily life, we see recommendation engines in action all around us, such as Spotify and Netflix.
Recommendation engines and learning are a natural fit. The process of seeing patterns in what an organisation or an individual needs, and then finding the right learning experience, is a core function of L&D. This is something a recommendation engine can do.
Marc uses a bit of machine learning jargon at one stage: collaborative filtering. A basic description of a collaborative filter is that it’s a series of techniques that looks at a user’s past actions and interests, and how they relate to those of other users, and makes recommendations based on user behaviour interrelationships.
Filtered’s platform is actually a combination of a chat and recommendation engine. Magpie is a version of this platform that has been designed specifically for L&D people. Magpie is a great way to experience what chatbots and recommendation engines can do.
To go along with the podcast series we have released an eBook with all transcripts of the interviews. To go along with the podcast series on How artificial intelligence is changing the way L&D is working, we have released an eBook with all transcripts of the interviews. The eBook also gives a brief explanation of what AI is and an overview of how it is being used in L&D.
Useful links