Recommendation systems are a collection of algorithms used to recommend items to users based on information taken from the user. These systems have become ubiquitous can be commonly seen in online stores, movies databases and job finders. Here, I will explore Content-based recommendation systems and implement a simple version of one using Python and the Pandas library.
This technique attempts to figure out what a user's favourite aspects of an item is, and then recommends items that present those aspects. In my case, I'm going to try to figure out the input's favorite genres from the movies and ratings given.
Dataset is acquired from GroupLens.
This model was implemented to complete the Machine Learning certification course.
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