Cracking the machine learning system design code - Part 1

Introductory Series on Engineering Machine Learning Systems.

Hello readers, I hope you're still intrigued about what's new in AI and that you nonetheless need us. Thank you for sticking with us and subscribing to our reading list.💖

• ML Ops evolved from the application of DevOps techniques to data science and machine learning workflows or pipelines.

• The word is a combination of ML (machine learning) and operations.

• It is, at its core, a repeatable procedure for deploying, monitoring, and maintaining these pipelines in operational or production systems.

  Companies that incorporate this type of rigorous thinking into their data science have a significant competitive edge over those that regularly fail to operationalize models and prioritize action above mere insight.

In this video, you’ll get to know me and get a few insights into what actual Machine Learning is about at the base.