This is a content based recommender system build by me. I used the approach of vectorization, bag of words technique. I have extracted tags from the whole dataset for each movie, and based on the tags the movies are being recommended.
** DATASET** TMDB The Movie Database, also known as TMDB, is a database that contains detailed information on over 500,000 movies. https://www.kaggle.com/tmdb/tmdb-movie-metadata
Cosine Similarity is:
a measure of similarity between two non-zero vectors of an inner product space the cosine of the trigonometric angle between two vectors the inner product of two vectors normalized to length 1 applied to vectors of low and high dimensionality not a measure of vector magnitude, just the angle between vectors