implicit_als_sparse_matrix_recommendation_quickstart.py

1import implicit
2from scipy.sparse import csr_matrix
3import numpy as np
4
5# load your data with your favorite package
6# (this example just creates a random sparse matrix)
7data = csr_matrix(np.random.random((100, 100)))
8
9# initialize a model
10model = implicit.als.AlternatingLeastSquares(factors=50)
11
12# train the model on a sparse matrix of user/item/confidence weights
13model.fit(data)
14
15# recommend items for a user
16userid = 0
17recommendations = model.recommend(userid, data[userid])
18
19# find related items
20itemid = 0
21related = model.similar_items(itemid)