MLOps a DevOps Culture for Machine Learning

What is MLOps and Why You Should Care?

MLOps is a DevOps in Machine Learning Project. Just imagine you have a project to build an AI 'empowered' software. You need to build the AI feature through machine learning approach. You should build model, test the model, and implement it into your software. There are extra steps you should fulfill and implement the MLOps means you can make sure that the machine learning activity can be well integrated with your DevOps.

MLOps = DevOps + ML Project

What is the key difference between MLOps and DevOps?

MLOps is an extra step in the DevOps. Therefore, some additional activity will be happened in MLOps. Here are the key deference's

  • MLOps is an iteration of experiment. MLOps provides additional iteration to experiment the model. You can put the experiment before the scrum sprint or includes it in the Scrum.
  • MLOps needs to be monitored. When building the model, you need to understand that the model itself need to be monitored carefully. Imagine you have a DGX1 to play with the dataset, you need to monitor the DGX 1 status with Azure Monitor.
  • MLOps needs automation before the model is built. Imagine you have dataset; you might need to pre-processing first. This extra step is part of MLOps
  • MLOps needs to handle model validation. MLOps doesn't use acceptance test, unit test, or code coverage. It uses different approaches. You might need validation set to validate your model. Doing some statistics measurement for error rate or something like that
  • MLOps needs a special member. MLOps might need more than software engine. Data Engineer, Data Science, or AI engineer can be part of MLOps

How do I get started with MLOps?

To get started in MLOps you should learn

  • You should learn how to build machine learning models. You can learn here for free
  • You should learn how to scale your AI solution and ML model. You can learn here for free.
  • You can see the implementation of MLOps here

Any Quick Reference for MLOps?

We have it for you, you can click to download the PDF file.

In the next post, we will learn MLOps in step-by-step.

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