Episode 30:How Deep Learning Based Recommendation System works in OTT Platforms?

Episode 30 of the Tech Stories podcast, hosted by amit bhatt, titled "Episode 30:How Deep Learning Based Recommendation System works in OTT Platforms?" was published on January 22, 2022 and runs 6 minutes.

January 22, 2022 ·6m · Tech Stories

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Summary

In this episode I narrate the story of recommendation system used by OTT Platforms, Social Medias and Video Platforms like YoutubeRecommendation SystemItem Based FilteringChoice Based RecommendationNetflix Recommendation EngineContent Based FilteringCollabaritive FilteringHow does OTT recommendation work?Custom recommendation system analyzes the past data history of a user and predicts the future insights that are more likely to engage the user.Cloud-based recommender systems help the OTT or VOD service providers in better understanding whether a service satisfies the user requirements or not.Which recommendation system next flix use?The Netflix Recommendation EngineTheir most successful algorithm, Netflix Recommendation Engine (NRE), is made up of algorithms which filter content based on each individual user profile.The engine filters over 3,000 titles at a time using 1,300 recommendation clusters based on user preferences.What is Content-based filtering?Content-based filtering uses item features to recommend other items similar to what the user likes, based on their previous actions or explicit feedback

Episode Description

In this episode I narrate the story of recommendation system used by OTT Platforms, Social Medias and Video Platforms like YoutubeRecommendation SystemItem Based Filtering

Choice Based Recommendation

Netflix Recommendation Engine

Content Based Filtering

Collabaritive FilteringHow does OTT recommendation work?Custom recommendation system analyzes the past data history of a user and predicts the future insights that are more likely to engage the user.Cloud-based recommender systems help the OTT or VOD service providers in better understanding whether a service satisfies the user requirements or not.Which recommendation system next flix use?The Netflix Recommendation EngineTheir most successful algorithm, Netflix Recommendation Engine (NRE), is made up of algorithms which filter content based on each individual user profile.The engine filters over 3,000 titles at a time using 1,300 recommendation clusters based on user preferences.What is Content-based filtering?Content-based filtering uses item features to recommend other items similar to what the user likes, based on their previous actions or explicit feedback