It didn’t all change in March 2020. Not really. The UK high street has been in the throes of a gradual revolution for decades. From the rise of ecommerce, to the birth of mobile, social commerce, and a growing emphasis on experience, change has been underway for a while. In fact for many, the pandemic has acted as a wake-up call. Digital transformation was no longer a ‘nice to have’ but a matter of survival. Necessity sparked innovation and customers are enjoying more flexibility and conveni ...
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055 - Recommendation Engines For Learning With Marc Zao - Sanders
MP3•Thuis aflevering
Manage episode 227487693 series 1291918
Inhoud geleverd door Learning While Working Podcast and Sprout Labs. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door Learning While Working Podcast and Sprout Labs of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.
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.
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continue reading
10 afleveringen
MP3•Thuis aflevering
Manage episode 227487693 series 1291918
Inhoud geleverd door Learning While Working Podcast and Sprout Labs. Alle podcastinhoud, inclusief afleveringen, afbeeldingen en podcastbeschrijvingen, wordt rechtstreeks geüpload en geleverd door Learning While Working Podcast and Sprout Labs of hun podcastplatformpartner. Als u denkt dat iemand uw auteursrechtelijk beschermde werk zonder uw toestemming gebruikt, kunt u het hier beschreven proces https://nl.player.fm/legal volgen.
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.
…
continue reading
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