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apex0data/ecommerce-fraud-detection-synthetic-10k-sampl

🛡️ Synthetic E-Commerce Fraud & AML Detection Dataset (10k Evaluation Sample) ⚠️ NOTICE: This is a truncated 10,000-row evaluation sample strictly for schema verification and local testing. 💳 [OBTAIN THE 10-MILLION ROW COMMERCIAL LICENSE HERE] > https://buy.stripe.com/8x26oIad4eH9eJf6gJ5wI01 🚀 Quick Start (Load via Hugging Face) Data scientists can instantly load this evaluation slice into their Pandas/Python environment using the datasets library: from… See the full description on the dataset page: https://huggingface.co/datasets/apex0data/ecommerce-fraud-detection-synthetic-10k-sampl.

sourceHugging Facemitupdated 7mo agoView on Hugging Face

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Dataset Card

🛡️ Synthetic E-Commerce Fraud & AML Detection Dataset (10k Evaluation Sample)

⚠️ NOTICE: This is a truncated 10,000-row evaluation sample strictly for schema verification and local testing.

💳 [OBTAIN THE 10-MILLION ROW COMMERCIAL LICENSE HERE] > [https://buy.stripe.com/8x26oIad4eH9eJf6gJ5wI01](https://buy.stripe.com/8x26oIad4eH9eJf6gJ5wI01)

🚀 Quick Start (Load via Hugging Face)

Data scientists can instantly load this evaluation slice into their Pandas/Python environment using the datasets library:

python

from datasets import load_dataset
import pandas as pd

# Load the 10k evaluation sample
dataset = load_dataset("apex0data/ecommerce-fraud-detection-synthetic-10k-sampl", split="train")
df = dataset.to_pandas()

print(df['is_fraud'].value_counts())