Scalable Attribution & Allocation as a Service

Advanced Matching Without Complexity

Our custom-trained machine learning models and proprietary algorithm identifies latent variables, assigns attributes, and clusters data based on your preferences. No need for manual tagging or rule-based matching – our system does the heavy lifting.

import kuhnelo
import pandas as pd

# Load the dataset
data = pd.read_csv('los_angeles_jobs.csv')

# Initialize the Kuhnelo client
client = kuhnelo.Client(api_key='db0c8bc8121b2091a42cc67e9986b9aa')

# Identify attributes in the dataset
attributes = client.identify_attributes(data)

# Upload the dataset with identified attributes
upload_response = client.upload_dataset(data, attributes)

# Make a call to select the top 5 clusters
clusters = client.get_top_clusters(upload_response['dataset_id'], top_n=5)

# Print the top 5 clusters
print(clusters)