Reference library

ML engineering pipelines

Feature prep, batch inference, model-serving hooks, and production ML workflow glue.

1 match
ML engineering pipelines medium

How to Mock ROC AUC in Python

Compute ROC AUC from scratch in Python using pairwise comparisons between positive and negative score distributions, ideal for testing ML models without sklearn.

machine-learning model-evaluation auc
Python
import random
from math import comb


def mock_roc_auc(scores, labels):
    """Compute mock ROC AUC by simulating a classifier's score distribution."""
    random.seed(42)
    n = len(labels)
    pos_scores = [scores[i] for i in range(n) if labels[i] == 1]
    neg_scores = [scores[i] for i in range(n) if labels[i] == …
12 0 Open

Browse by section

Each section groups closely related Python snippets.

ML engineering pipelines — Python code examples

What you will find here

This page collects ml engineering pipelines snippets — short, copy-ready Python you can paste into our free online IDE and run without installing anything. Each sample includes a plain-English explanation and the full source code.

Samples vs tutorials and challenges

Samples are quick reference — one concept per page. For step-by-step teaching, use our Python tutorials. To test yourself, try quizzes or coding challenges. Clean up style with the Python formatter.