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Developer Guide
SDKs
Python SDK - Fake Detection

Python SDK - Fake Detection

Algorithm
Classifier
Use Cases
Fake Profile Detection, Fraud Detection, Strange Behaviour Detection

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 “Fake Detection”
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

bg.config("app_id", "secret_key")
 
To use your trained algorithm, input the following code

import begin as bg

bg.config("app_id", "secret_key")

bg.infer('PROJECT_ID', {user_details_object})

Out: {"fake_probability": 0.98}
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.
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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.