KevinLiao159

def make_recommendations(self, fav_movie, n_recommendations):
    """
    make top n movie recommendations
    Parameters
    ----------
    fav_movie: str, name of user input movie
    n_recommendations: int, top n recommendations
    """
    # get data
    movie_user_mat_sparse, hashmap = self._prep_data()

KevinLiao159

def make_recommendations(self, fav_movie, n_recommendations):
    """
    make top n movie recommendations
    Parameters
    ----------
    fav_movie: str, name of user input movie
    n_recommendations: int, top n recommendations
    """
    # get data
    movie_user_mat_sparse, hashmap = self._prep_data()

KevinLiao159

from pyspark.ml.recommendation import ALS


def tune_ALS(train_data, validation_data, maxIter, regParams, ranks):
    """
    grid search function to select the best model based on RMSE of
    validation data

    Parameters
    ----------