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ML engineering pipelines

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

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Bayesian Optimization in Python: A Simplified Mock Implementation

A toy Bayesian optimization loop with a Gaussian process prior, expected improvement acquisition, and noisy sampling to find a function's minimum.

bayesian-optimization gaussian-process hyperparameter-tuning

Python

import random
import math

class BayesianOptimizer:
    def __init__(self, noise=0.1):
        self.noise = noise
        self.observations = []
    
    def objective(self, x):
        return (math.sin(3*x) + 0.5*x) / (1 + x**2)
    
    def gaussian_process_prior(self, x1, x2, length_scale=0.5):
        return math.…

12 0 Open

ML engineering pipelines medium

How to Mock Kedro Pipeline Nodes in Python

Create a modular Kedro pipeline with node functions, namespacing, and input/output mapping to mock pipeline execution locally.

kedro pipeline modular

Python

from kedro.pipeline import Pipeline, node
from kedro.pipeline.modular_pipeline import pipeline as modular_pipeline


def preprocess(data: list) -> list:
    """Clean data by removing None values."""
    return [item for item in data if item is not None]


def transform(data: list) -> list:
    """Add 1 to each numeric…

15 0 Open

ML engineering pipelines medium

How to Mock a Kubeflow Pipeline in Python

Build a minimal in-memory mock of a Kubeflow pipeline DAG using dataclasses and OrderedDict to chain component functions.

kubeflow pipelines mlops

Python

from typing import Dict, Any
from dataclasses import dataclass, field
from collections import OrderedDict


@dataclass
class KubeflowPipelineMock:
    """A minimal mock of a Kubeflow pipeline DAG."""
    name: str
    components: OrderedDict[str, callable] = field(default_factory=OrderedDict)

    def add_component(se…

14 0 Open

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