Timecodes for "MLOps Zoomcamp 5.1 - Intro to ML monitoring"

[alexeygrigorev]

Timecodes for "MLOps Zoomcamp 5.1 - Intro to ML monitoring"

[dimzachar]

Summary:
Hello and welcome to this video on monitoring machine learning models in production. In this video, we will cover the basics of monitoring machine learning models in production environments. We will start by discussing the importance of monitoring and the metrics that are used to measure the performance and quality of data. Next, we will explore how existing monitoring architecture can be reused for machine learning models. Finally, we will introduce the concept of batch monitoring pipelines for machine learning models. By the end of this video, you will have a good understanding of how to monitor machine learning models in production environments and ensure that they are performing optimally. So, let's get started!

Key Takeaways:

• The video covers the basics of monitoring machine learning models in production environments
• It discusses the importance of monitoring and the metrics used to measure performance and quality of data
• It also explores reusing existing monitoring architecture for machine learning models and introduces the concept of batch monitoring pipelines
• The video aims to provide a good understanding of how to monitor machine learning models in production environments to ensure optimal performance.

Timestamps:
0:00:00 - Introduction to monitoring machine learning models in production.
0:03:00 - Metrics for model performance and data quality.
0:06:06 - Reuse existing monitoring architecture for machine learning.
0:09:14 - Batch monitoring pipeline for machine learning models.

[amitfrancis]

Updated timecodes. Thank you!