► Grab your MLOps roadmap here: ► Ready to land a higher-paying role? Book a free call to see if our DevOps bootcamp fits your career goals: Everything you need to know about MLOps (Machine Learning Operations)! I'll explain what MLOps is, why it's essential, and how it solves real-world problems when deploying ML models to production. ▬▬▬▬▬▬ Thanks Warp for making this video possible 🙌 ▬▬▬▬▬▬ ► Warp is the fastest way to build with multiple AI agent ► Try Warp for free today → ▬▬▬▬▬▬ What You'll Learn 🧠 ▬▬▬▬▬▬ - What MLOps is and why it's necessary for ML systems - Real-world challenges when deploying ML models (using a banking fraud detection example) - How MLOps differs from traditional software development - Key MLOps concepts: containerization, CI/CD pipelines, monitoring, and data drift - Essential MLOps tools: Docker, Kubernetes, MLflow, TensorFlow Data Validation, Prometheus, Grafana, and more - Complete MLOps workflow from data collection to production deployment - Who needs to learn MLOps: Data Scientists, DevOps Engineers, Cloud Engineers, and Engineering Managers ▬▬▬▬▬▬ T I M E S T A M P S ⏰ ▬▬▬▬▬▬ 00:00 - Intro 00:39 - Understanding the problem - Why we need MLOps 04:30 - How MLOps solves this 10:08 - Why MLOps Became Necessary 11:42 - MLOps Tools and Implementation 18:01 - What Does an MLOps Workflow Look Like 20:52 - Who Needs To Learn MLOps ▬▬▬▬▬▬ Connect with me 👋 ▬▬▬▬▬▬ INSTAGRAM ► TWITTER ► LINKEDIN ► MLOps Explained | What is MLOps | MLOps Tutorial | What is Machine Learning Operations | What is AI Operations