MLOps - Introduction | Learn MLOps In Simple Way | EP 1

🎥 MLOps - Introduction
🔍 Dive into the fascinating world of MLOps (Machine Learning Operations) in this comprehensive introductory video!

What You'll Learn

🚀 What is MLOps?
MLOps is a set of practices to design, deploy, maintain, and monitor ML models continuously and efficiently across various environments.

📜 Origin of MLOps:
Inspired by DevOps principles introduced in the late 2000s.
Challenges in scaling and reproducibility during the rise of ML in the 2010s.
Standardized practices emerging between 2015–2020 with tools like MLflow, Kubeflow, and TFX.

🔄 ML Lifecycle Overview:
Design: Problem definition, EDA, and implementation design.
Development: Feature engineering, experiment design, and model training.
Deployment: CI/CD setup, model deployment, and monitoring.

💡 MLOps Lifecycle in Action:
Data Preparation and EDA.
Model development, training, and retraining.
Deployment, inference, and monitoring in production.

Why Watch This Video?
Gain clarity on how MLOps enables scalable, reproducible, and efficient ML operations.
Understand how MLOps aligns with the traditional ML lifecycle to achieve reliable production systems.
Who Is This Video For?
DevOps professionals looking to explore MLOps.
Beginners who want to understand the foundational concepts of MLOps and ML lifecycle.

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#MLOps #MachineLearning #DevOps #MLLifecycle #AI #DataScience #Kubernetes #MLflow

Видео MLOps - Introduction | Learn MLOps In Simple Way | EP 1 канала Sandip Das
cloud, learn_with_sandip, devops