K
Kathleen Martin
Guest
You have probably heard of the term DevOps already, as well as machine learning and artificial intelligence. DevOps was first introduced a decade ago as a practice that seeks to unite developers and IT operations to collaborate better. However, as the volume of data became more and more unmanageable for normal human capacity, the use of artificial intelligence and machine learning, therefore, became a more pressing necessity. After all, we live in the golden age of digitization and technology.
This is where MLOps came into existence.
What Is MLOps?
One can say that MLOps is just a level higher than DevOps. It is its expected evolution. In a nutshell, MLOps is similar to DevOps in that it is a practice that involves software developers and IT operations teams with the addition of data scientists and ML and AI experts. They seek to find useful applications of the various technologies available, particularly in creating models and ensuring their efficiency.
Why Do Companies Need to Consider MLOps?
While machine learning is a valued addition to any company’s tech arsenal, the actual application, and much more, its productization still proves to be a challenge. After all, the production process with machine learning involves multiple components from data collection, data prep and analysis, model creation, model review, and more. Thus, it will require collaboration among various teams to make it possible.
The Benefits of MLOps
There are different advantages to having MLOps. Here are three:
Efficiency
The first reason why you should consider MLOps is the efficiency that it can bring to your company. MLOps allows data scientists to focus on their tasks more and achieve the faster development and deployment of their machine learning models.
Continue reading: https://www.iotforall.com/why-companies-need-to-think-about-mlops
This is where MLOps came into existence.
What Is MLOps?
One can say that MLOps is just a level higher than DevOps. It is its expected evolution. In a nutshell, MLOps is similar to DevOps in that it is a practice that involves software developers and IT operations teams with the addition of data scientists and ML and AI experts. They seek to find useful applications of the various technologies available, particularly in creating models and ensuring their efficiency.
Why Do Companies Need to Consider MLOps?
While machine learning is a valued addition to any company’s tech arsenal, the actual application, and much more, its productization still proves to be a challenge. After all, the production process with machine learning involves multiple components from data collection, data prep and analysis, model creation, model review, and more. Thus, it will require collaboration among various teams to make it possible.
The Benefits of MLOps
There are different advantages to having MLOps. Here are three:
Efficiency
The first reason why you should consider MLOps is the efficiency that it can bring to your company. MLOps allows data scientists to focus on their tasks more and achieve the faster development and deployment of their machine learning models.
Continue reading: https://www.iotforall.com/why-companies-need-to-think-about-mlops
