MLOps Explained - What It Is, Why You Need It and How It Works
► Grab your MLOps roadmap here: https://bit.ly/43IQO9N ► Ready to land a higher-paying role? Book a free call to see if our DevOps bootcamp fits your career goals: https://bit.ly/4oynnzQ 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 → https://go.warp.dev/nanaytagents ▬▬▬▬▬▬ 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 - Comp
Watch on TechWorld with Nana
Opens in a new tab




