Movie recommendation system - Python Language

Movie recommendation system: A movie recommendation system can be created by using a dataset of movies and their attributes, and then using a machine learning algorithm to predict which movies a user would like based on their viewing history.

Here is a sample code for a Movie recommendation system:

This code uses the Pandas library to read a CSV file containing the movie data and uses the sklearn library to calculate the cosine similarity between movies based on the keywords, cast, genres, and director. The code uses a Tf-idf vectorizer to convert the movie data into a numerical matrix, and cosine similarity is calculated between the movies based on the matrix. Then it prompts the user to enter a movie title and finds the movie in the dataset and then finds the most similar movies to the input movie by sorting the movies based on the cosine similarity and prints the movie title.

Good Luck!