Project 2: Movie Recommendation Engine

• Imported a movie dataset csv file and used sklearn and machine learning algorithms to recommend movies based off your inputed favorite.
• Engineered features to use in the algorithm: “overview”, “keywords”, “cast”, “genres”, “director”.
• Combined the features into one string and used CountVectorize to convert the collection of text to token counts
• Used the Cosine Similarity to create a matrix showing the similar movies based off the features combined
• Created a function to be able to look through then index of movies to return a movie title that matches the similarity index.
• Returns the top ‘n’ movies based off your inputed ‘favorite movie’.