Recommender Systems with Machine Learning - Making Recommendations

The video tutorial explains how to create a content-based movie recommender function. It covers defining the function, taking inputs, calculating closest titles and distance scores, and filtering and sorting similar movies. The tutorial concludes with running the function using an example and previews the next video on collaborative and item-based filtering.

Describe the process of filtering similar movies in the function.

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What is the significance of the 'how many' variable in the function?

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What genre is the recommendation based on when using the function with 'Jumanji'?

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