Introduction to MLOps: What, Why, and How

Explore the fundamentals of MLOps in this 56-minute video lecture. Delve into the importance of MLOps, its challenges, and how it differs from DevOps. Learn about reusable pipelines, continuous training, and the MLOps lifecycle. Discover the benefits of implementing MLOps practices and how they address common challenges in AI/ML projects. Gain insights into data science aspects such as skewness and model statistics. Watch a practical demonstration of an MLOps pipeline and automation techniques. Understand how MLOps can streamline AI/ML processes, reduce time-to-market, and improve overall efficiency in machine learning projects.

Introduction
Why MLOps
Survey
Challenges
MLOps
MLOps vs DevOps
Reusable Pipeline
ML Example
Benefits
MLOps Lifecycle
Continuous Training
Skewness
Data Science
Demo
Pipeline
Model
Stats
Automation
Joke