Reference library

ML engineering pipelines

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

3 matches

How to Build a Simple ML Pipeline with ZenML in Python

Build a mock machine learning pipeline with ZenML steps for data loading, training, and evaluation, and run it to print the final accuracy.

zenml ml pipeline

Python

from zenml import pipeline, step


@step
def load_data() -> dict:
    """Simulate loading data from a source."""
    return {"accuracy": 0.0, "loss": 1.0}


@step
def train_model(data: dict) -> dict:
    """Simulate training a model."""
    data["accuracy"] = 0.95
    data["loss"] = 0.1
    return data


@step
def eva…

13 0 Open

ML engineering pipelines easy

How to Save and Load PyTorch Model State Dict in Python

This code demonstrates how to save a PyTorch model's state dict to a file and load it back into a new model instance, verifying weights match.

pytorch state-dict model

Python

import torch
import torch.nn as nn

class SimpleNet(nn.Module):
    def __init__(self):
        super().__init__()
        self.fc1 = nn.Linear(4, 8)
        self.fc2 = nn.Linear(8, 2)

    def forward(self, x):
        x = torch.relu(self.fc1(x))
        return self.fc2(x)

if __name__ == "__main__":
    model = Simp…

13 0 Open

ML engineering pipelines easy

Load CSV Training Data Without Pandas in Python

This code loads a CSV file into a list of dictionaries using only the standard library, ideal for small ML training data without heavy dependencies.

csv data-loading standard-library

Python

import csv
from pathlib import Path

def load_csv(path):
    """Load CSV file into list of dicts without pandas."""
    rows = []
    with open(path, newline='', encoding='utf-8') as f:
        reader = csv.DictReader(f)
        for row in reader:
            rows.append(dict(row))
    return rows

if __name__ == "__m…

13 0 Open

Browse by section

Each section groups closely related Python snippets.