MLOps: A Review

08/19/2023
by   Samar Wazir, et al.
0

Recently, Machine Learning (ML) has become a widely accepted method for significant progress that is rapidly evolving. Since it employs computational methods to teach machines and produce acceptable answers. The significance of the Machine Learning Operations (MLOps) methods, which can provide acceptable answers for such problems, is examined in this study. To assist in the creation of software that is simple to use, the authors research MLOps methods. To choose the best tool structure for certain projects, the authors also assess the features and operability of various MLOps methods. A total of 22 papers were assessed that attempted to apply the MLOps idea. Finally, the authors admit the scarcity of fully effective MLOps methods based on which advancements can self-regulate by limiting human engagement.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/01/2023

A Comprehensive Study of Groundbreaking Machine Learning Research: Analyzing Highly Cited and Impactful Publications across Six Decades

Machine learning (ML) has emerged as a prominent field of research in co...
research
01/08/2022

Machine Learning-Based Disease Diagnosis:A Bibliometric Analysis

Machine Learning (ML) has garnered considerable attention from researche...
research
03/20/2018

The Three Pillars of Machine-Based Programming

In this position paper, we describe our vision of the future of machine-...
research
03/20/2018

The Three Pillars of Machine Programming

In this position paper, we describe our vision of the future of machine ...
research
04/13/2018

Machine Learning in Astronomy: A Case Study in Quasar-Star Classification

We present the results of various automated classification methods, base...
research
02/21/2022

Machine Learning Operations: A Survey on MLOps Tool Support

Machine Learning (ML) has become a fast-growing, trending approach in so...

Please sign up or login with your details

Forgot password? Click here to reset