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Python 3
K-Nearest Neighbors Algorithm

K-Nearest Neighbors Algorithm

K-Nearest Neighbors Algorithm

K-Nearest Neighbors Algorithm

K-Nearest Neighbors (KNN) is an algorithm that finds items that are most similar to a given input. It works by comparing data points and measuring the distance between them.
In this project, KNN compares the TF-IDF vectors of movies and calculates their similarity using cosine similarity. When a user selects a movie, the algorithm searches for movies with vectors that are closest to the selected movie.
The closest movies are considered the most similar and are recommended to the user. This approach makes the recommendation process straightforward and easy to understand.

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K-Nearest Neighbors Algorithm

Contents

K-Nearest Neighbors Algorithm

Movie Recommendation System Project Using Content-Based Filtering

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