techiescamp

techiescamp / mlops-for-devops

Public

MLOps for DevOps Engineers - A hands-on, project-based guide to Machine Learning Operations

devopscube.comdevops-to-mlops devops devops-mlops mlops mlops-project
130
62
100% credibility
Found Feb 24, 2026 at 55 stars 2x -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

A tutorial repository teaching DevOps engineers MLOps concepts through hands-on local data preparation for an employee attrition prediction project.

How It Works

1
🔍 Discover the Guide

You find a helpful online guide designed for people who manage tech systems and want to learn about smart prediction tools without needing a math degree.

2
📖 Dive into the Basics

You read simple stories and examples that feel familiar from your everyday work, getting excited about predicting if employees might leave a company.

3
🛠️ Prepare Your Computer

You make sure your setup is ready by checking a few basic skills like using simple commands and files, all explained plainly.

4
🔄 Run the Data Magic

You follow easy numbered steps to load company employee info, check it for issues, explore patterns with fun charts, clean it up, smarten it with new insights, and split it into practice and test sets – seeing results appear right away!

5
📁 Check Your Ready Data

You look at the neatly organized folders with your freshly prepared data, perfect for the next part of building predictions.

🎉 You've Built Your First Smart Pipeline!

Hooray! Now you have a working flow on your own computer to handle real employee data like the experts, ready for more advanced steps ahead.

Sign up to see the full architecture

4 more

Sign Up Free

Star Growth

See how this repo grew from 55 to 130 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is mlops-for-devops?

This Python-based repo delivers a hands-on MLOps course for DevOps engineers, walking you through building ML data pipelines locally for predicting employee attrition—no prior ML knowledge needed. It uses familiar tools like Pandas, scikit-learn, and DVC to ingest, validate, explore, clean, feature-engineer, and preprocess datasets, drawing DevOps analogies to explain the difference between DevOps and MLOps. You get a runnable project that mirrors production ML workflows, prepping you for Kubernetes deployment in later phases.

Why is it gaining traction?

It stands out as an MLOps roadmap tailored for DevOps and SRE roles, skipping data science theory for infrastructure-focused steps like pipeline automation with GitHub Actions. DevOps engineers grab it for the real-world use case and clear prerequisites (Docker, K8s basics), making the MLOps for DevOps engineer transition feel like extending your CI/CD skills to AI Ops and Data Ops. Early adopters praise the practical scripts that output processed data and model artifacts ready for serving.

Who should use this?

DevOps engineers eyeing MLOps DevOps jobs or higher salaries via certifications like AWS ML Engineer. Platform teams handling ML workloads in Kubernetes without becoming data scientists. SREs building internal LLM tools or monitoring pipelines on existing stacks.

Verdict

Solid starter for an MLOps GitHub tutorial aimed at DevOps—run phase 1 today for local pipelines, but with just 16 stars and 1.0% credibility score, it's early-stage; watch for upcoming deployment phases before production use. Worth starring if you're on the MLOps DevOps roadmap.

(178 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.