Delivering micro-content (small pieces of learning materials) from a course catalog\u00a0has become important as it helps learners engage quickly with a learning platform\u00a0on a need-to-know period. In order to recommend videos that can teach skills\u00a0relevant to a learner, we propose an approach for tagging videos with skills using\u00a0transcripts. Since there is no labeled data to train a video-to-skill model directly,\u00a0we leverage a bunch of techniques that fall under the umbrella of weak supervision.\u00a0We evaluate our approach using offline metrics like Precision, Recall, F-1 score\u00a0and online metrics via large-scale A\/B testing.<\/p>\n","protected":false},"excerpt":{"rendered":"
Delivering micro-content (small pieces of learning materials) from a course catalog\u00a0has become important as it helps learners engage quickly with a learning platform\u00a0on a need-to-know period. In order to recommend videos that can teach skills\u00a0relevant to a learner, we propose an approach for tagging videos with skills using\u00a0transcripts. 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