From the course: Building Recommender Systems with Machine Learning and AI

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Implement random exploration

Implement random exploration - Python Tutorial

From the course: Building Recommender Systems with Machine Learning and AI

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Implement random exploration

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- [Instructor] As an exercise, try your hand at implementing random exploration. Go back the Evaluate Users CFScript way back in the Collaborative Filtering section of the course. It generated top 10 recommendations for every user with user-based KNN and measured the hit rate. Your challenge is to modify this code, especially at the last slot in your top 10 recommendations is always used to surface a random movie that was released in the most current year in the Movie Lines data set. To do this, you'll have to modify our Movie Lines module to identify and extract movies in the most current year it has and modify the Evaluate Users CFScript to replace the 10th slot in each users recommendations with one of these movies chosen at random. See what impact it actually has on the hit rate. If it doesn't impact hit rate much, then it might be a reasonable thing to do if you have a real problem with new movies not being surfaced to users quickly enough. Up next, I'll review my solution to…

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