Problem:
I need on building recommender systems to find music that interest users.
Solution:
I built a personalized model, and showed the significant improvement provided by personalization. I’m going to explore the song data and the recommendations made by my model.
Download:
Start:
# Use Graphlab library
import graphlab
# Use Sframe of Graphlab to load data
song_data = graphlab.SFrame('song_data.gl/')
# Create Users to contain all users are unique
users = song_data['user_id'].unique()
# Create Train Data, Test Data
train_data,test_data = song_data.random_split(.8,seed=0)
# Use similarity recommender
personalized_model = graphlab.item_similarity_recommender.create(train_data,
user_id='user_id',
item_id='song')
# Use the persionalized model to find similar songs to any song in the dataset
personalized_model.get_similar_items(['With Or Without You - U2'])
#the personalized model to make song recommendations personalized_model.recommend(users=[users[0]])
