Reference library

ML engineering pipelines

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

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K-Fold Cross Validation in Python: A Simple Implementation

Implements k-fold cross validation from scratch, splitting data into folds and computing MSE scores for a baseline mean-predictor model.

cross-validation ml model-evaluation
Python 
import random
from statistics import mean


def cross_validation_scores(data, labels, k=5, seed=42):
    random.seed(seed)
    indices = list(range(len(data)))
    random.shuffle(indices)
    fold_size = len(indices) // k
    folds = []
    for i in range(k):
        if i == k - 1:
            folds.append(indices[i *…
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