def get_similar_movies(movie_title, n_ratings_filter=100, n_recommendations=5):
    similar = matrix.corrwith(matrix[movie_title])
    corr_similar = pd.DataFrame(similar, columns=['correlation'])
    corr_similar.dropna(inplace=True)

    orig = data.copy()

    corr_with_movie = pd.merge(
        left=corr_similar,
        right=orig,
        on='title')[['title', 'correlation', 'numRatings']].drop_duplicates().reset_index(drop=True)

    result = corr_with_movie[corr_with_movie['numRatings'] > n_ratings_filter].sort_values(by='correlation', ascending=False)

    return result.head(n_recommendations)