Real-World MLOps in Action – A Case Study Deep Dive

🧠 Ever wondered how ML models go from Jupyter Notebooks to powering recommendations for millions?

🛠️ This Meetup pulls back the curtain on the full MLOps lifecycle – not in theory, but through a real-world production case study.

### 🔥 Case Study: Real-Time Fraud Detection System in a Fintech Platform

(A real MLOps implementation inspired by industry practices at companies like PayPal, Razorpay, and Stripe)

#### ⚡ Problem:

Catch fraudulent transactions (money laundering, account takeover, bot attacks) in real-time — with millions of events coming in per day.

### 🔥 Live Demo :

• How a fraudulent transaction gets scored in real-time
• Auto model promotion from staging to production
• Detecting model drift using live dashboards
• Retraining trigger via scheduled job (Airflow)

### 🎁 You’ll Get:

• 🧾 Coderrange MLOps CaseSheet PDF: Tools, pipelines, CLI commands
• ⚡ GitHub mini-repo: Sample CI/CD for ML model
• 🔄 YAML templates for model deployment with KServe
• 🧠 Prompt template for evaluating models using LLM (bonus!)

### 👥 Meetup Audience Fit:

• ML Engineers & Data Scientists
• Backend Devs curious about ML in prod
• DevOps & Platform Engineers
• Anyone building AI/ML powered apps

MLOps isn't just DevOps + ML. It's how AI scales.

Join Zoom Meeting

https://us02web.zoom.us/j/84051225949?pwd=e5HcBOm6YpQK3ADTceWRwoCA3zAKT9.1

Meeting ID: 840 5122 5949
Passcode: 437789