Pipeline Automation

Pipeline automation refers to the process of streamlining and automating workflows in data science and software development. By integrating various tasks into a cohesive pipeline, it allows for efficient data processing, model training, and deployment. This approach minimizes manual intervention, reduces errors, and enhances productivity. Pipelines can encompass a range of activities, including data cleaning, feature selection, model training, and validation. They enable teams to rapidly iterate through different models and configurations, ultimately leading to more scalable and maintainable systems. Overall, pipeline automation is essential for modern data-driven projects, ensuring consistency and reliability in results.

Automated Machine Learning with Sklearn Pipelines

Towards Data Science

Pipelines provide the structure to automate training and testing models. They can incorporate column transformations, scaling, imputation, feature selection, and hyperparameter searches. Abstracting…

How I Built Full Automation Pipelines with Python

Python in Plain English

1. Why I Outgrew “Small Scripts” After months of writing small automation scripts — cleaning folders, sending emails, parsing CSVs — I realized something: these were great, but isolated . Each script ...

Pipelines

Kaggle Learn Courses

In this tutorial, you will learn how to use **pipelines** to clean up your modeling code. Introduction **Pipelines** are a simple way to keep your data preprocessing and modeling code organized. Speci...

Pipelines

Kaggle Learn Courses

Pipelines

Kaggle Learn Courses

Pipeline and Custom Transformer with a Hands-On Case Study in Python

Towards Data Science

Pipelines in machine learning involve converting an end-to-end workflow into a set of codes to automate the entire data treatment and model development process. We can use pipelines to sequentially…

Pipelines: Automated machine learning with HyperParameter Tuning!

Towards Data Science

Introduction to Machine learning automation using Sklearn Pipelines. We will walk through the basic steps towards custom transformer classes!

REST APIs — The Silver Bullet in Pipeline Automation

Better Programming

As we know, there is no silver bullet in IT. Crowning REST APIs as the silver bullet in pipeline automation is only meant to emphasize the great potential REST APIs can bring for the whole automation…...

The Automation Pipeline That Changed My Daily Routine Forever

Python in Plain English

I didn’t wake up one day and decide to become a productivity machine. It actually started out of frustration. Every morning, I’d waste 30–40 minutes just doing the same exact things: Opening folders a...

Automating Data CI/CD for Scalable MLOps Pipelines

Towards AI

Member-only story Automating Data CI/CD for Scalable MLOps Pipelines A step-by-step guide to achieving continuous data integration and delivery in production ML systems Kuriko Iwai 16 min read · Just ...

Building an Automated Machine Learning Pipeline: Part Four

Towards Data Science

Automate your Machine Learning pipeline with Docker, Luigi and Python. Integrate and run each step of the Machine Learning Pipeline.

Scientific Data Analysis Pipelines and Reproducibility

Towards Data Science

Pipelines are computational tools of convenience. Data analysis usually requires data acquisition, quality check, clean up, exploratory analysis and hypothesis driven analysis. Pipelines can automate…...