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/81605651117?pwd=b9aTv5t9nksSB03DVGRXixSuxYSQzV.1](https://www.google.com/url?q=https://us02web.zoom.us/j/81605651117?pwd%3Db9aTv5t9nksSB03DVGRXixSuxYSQzV.1&sa=D&source=calendar&usd=2&usg=AOvVaw1LWcNPhwU35Linka3iRRMO)
Meeting ID: 816 0565 1117
Passcode: 861884