Documentation
Developer Guide
SDKs
Python SDK - Recommender

Python SDK - Recommender

Algorithm
Recommender
Use Cases
Content Recommender, Game recommenders, Price category recommenders, Product recommender, Service Recommenders, etc.
Visit Github for an example of Goodreads data:
demo-pysdk/Get recommendations for users.ipynb at main · Begin-AI/demo-pysdk
Contribute to Begin-AI/demo-pysdk development by creating an account on GitHub.
demo-pysdk/Get recommendations for users.ipynb at main · Begin-AI/demo-pysdk
https://github.com/Begin-AI/demo-pysdk/blob/main/goodreads/Get%20recommendations%20for%20users.ipynb
demo-pysdk/Get recommendations for users.ipynb at main · Begin-AI/demo-pysdk

Prerequisites

Before you reach this stage, ensure you’ve:
  1. Created a schema
  1. Integrated code to process your data and installed Begin’s Python SDK
  1. Created a project with the objective “Recommender”
Learning usually takes about 30 minutes. Once complete, your machine learning algorithm is ready to be used on your mobile device, browser, connected vehicles, or server applications.

Procedure

In order to fetch recommendations, follow the initialization step:

import Begin as bg

applier = bg.AlgorithmsApplier(app_id=APP_ID, license_key=LICENSE_KEY)
 
To use your trained algorithm, input the following code

applier.recommend(project_id = PROJECT_ID, user_id = USER_ID, 
	limit = 10, page = 1)

Out: [{'object_id': '25190693',
  'person_id': '11',
  'similarity': 0.7192863865075461}, ... ]
 
This will return the recommended list of IDs for the given user.
 
If you performed the initial processing in Python, you can still use the algorithm with other SDKs like Android or iOS SDKs.
 
💡
Note: Begin’s algorithms can learn continuously with additional user data while your code is deployed. Your project can learn from datasets on your mobile application, server or other applications without you having to worry about merging the learning or merging the data. Begin will take care of merging the learning.