Quick Start¶

Install¶

Install ads using pip (shown below) or OCI Conda Packs

python3 -m pip install "oracle_ads"

Initialize¶

Initialize your recommender job through the ads cli command:

ads operator init -t recommender

Prepare Input Data¶

The Recommender Operator requires three essential input files:

Users File: Contains user information.
Items File: Contains item information.
Interactions File: Interactions between users and items.

Sample Data¶

users.csv:

user_id	age	gender	occupation	zip_code
1	24	M	technician	85711
2	53	F	other	94043
3	23	M	writer	32067
4	24	M	technician	43537
5	33	F	other	15213

items.csv:

movie_id	movie_title	release_date	Action	Adventure	Animation	Children
1	Toy Story (1995)	01-Jan-1995	0	0	1	1
2	GoldenEye (1995)	01-Jan-1995	1	1	0	0
3	Four Rooms (1995)	01-Jan-1995	0	0	0	0
4	Get Shorty (1995)	01-Jan-1995	1	0	0	0

interactions.csv:

user_id	movie_id	rating	timestamp
2	1	3	881250949
4	2	3	891717742
3	3	1	878887116
1	4	2	880606923
5	2	1	886397596
2	3	4	884182806
4	1	2	881171488

Configure the YAML File¶

Within the recommender folder created above there will be a recommender.yaml file. This file should be updated to contain the details about your data and recommender.

cd recommender
vi recommender.yaml

kind: operator
type: recommendation
version: v1
spec:
  user_data:
    url: users.csv
  item_data:
    url: items.csv
  interactions_data:
    url: interactions.csv
  top_k: 4
  user_column: user_id
  item_column: movie_id
  interaction_column: rating

Run the Recommender Operator¶

Now run the recommender job locally:

ads operator run -f recommender.yaml

Results¶

If not specified in the YAML, all results will be placed in a new folder called results. Performance is summarized in the report.html file, and the recommendation results can be found in results/recommendations.csv.

vi results/recommendations.csv
open results/report.html

Example Output (recommendations.csv):¶

user_id	movie_id	rating
1	1	4.9424
1	2	4.7960
1	3	4.7314
1	4	4.6951
2	1	4.7893
2	2	4.7870
2	3	4.7624
2	4	4.6802