A simple NLP algorithm for recommending movies
Summary: In this project I developed a simple movie recommendation system, that returns the top 10 movies base on a given movie title.
- Load csv/text files containing your movie titles and the plot/overview of each movie
- Merge the two csvfiles based on id and remove all rows with nan's
- Import TfidfVectorizer (Term frequency Inverse Document frequency) module from sklearn
- Create tfv using TfidfVectorizer and apply the fit_transform to obtain the tfv_matrix
- Compute the Sigmoid kernel scores