Demystifying Machine Learning Operations (MLOps)
Managing the machine learning process using recommended practices is a must to enable collaboration, tracing, and real-time monitoring. This course will teach you what are the main concerns and issues you need to consider while developing a machine learning model and after deploying it.
What you'll learn
Machine Learning is a robust science that can empower the business with unique competitive advantages to address several challenges, such as sales price prediction, customer segment classification, and product recommendation. In this course, Demystifying Machine Learning Operations (MLOps), you’ll learn to implement machine learning operations into your machine learning project. First, you’ll explore how to apply machine learning operations (MLOps) practices for your infrastructure. Next, you’ll discover how machine learning operations (MLOps) during model development. Finally, you’ll learn how to apply machine learning operations (MLOps) after model deployment. When you’re finished with this course, you’ll have the skills and knowledge of machine learning operations needed to manage the MLOps lifecycle of your project.
Table of contents
- Overview 2m
- Describing the Business Problem 3m
- Demo: Presenting Your Prototype 7m
- Moving to Production 5m
- Understanding MLOps Infrastructure 4m
- Demo: Pushing Bootstrapped Project 6m
- Challenges Fixed by Source Control 1m
- Demo: Creating Infrastructure as a Code - Part 1 5m
- Demo: Creating Infrastructure as a Code - Part 2 5m
- Challenges Fixed by Infrastructure as a Code 1m
- Summary 3m