DeepAI AI Chat
Log In Sign Up

Towards Modular Machine Learning Solution Development: Benefits and Trade-offs

by   Samiyuru Menik, et al.
University of Georgia

Machine learning technologies have demonstrated immense capabilities in various domains. They play a key role in the success of modern businesses. However, adoption of machine learning technologies has a lot of untouched potential. Cost of developing custom machine learning solutions that solve unique business problems is a major inhibitor to far-reaching adoption of machine learning technologies. We recognize that the monolithic nature prevalent in today's machine learning applications stands in the way of efficient and cost effective customized machine learning solution development. In this work we explore the benefits of modular machine learning solutions and discuss how modular machine learning solutions can overcome some of the major solution engineering limitations of monolithic machine learning solutions. We analyze the trade-offs between modular and monolithic machine learning solutions through three deep learning problems; one text based and the two image based. Our experimental results show that modular machine learning solutions have a promising potential to reap the solution engineering advantages of modularity while gaining performance and data advantages in a way the monolithic machine learning solutions do not permit.


page 5

page 6

page 8


Components of Machine Learning: Binding Bits and FLOPS

Many machine learning problems and methods are combinations of three com...

Agility in Software 2.0 – Notebook Interfaces and MLOps with Buttresses and Rebars

Artificial intelligence through machine learning is increasingly used in...

Constrained Multi-Objective Optimization for Automated Machine Learning

Automated machine learning has gained a lot of attention recently. Build...

Explainable Machine Learning for Fraud Detection

The application of machine learning to support the processing of large d...

Is a Modular Architecture Enough?

Inspired from human cognition, machine learning systems are gradually re...

Bridging belief function theory to modern machine learning

Machine learning is a quickly evolving field which now looks really diff...

Confidential Machine Learning on Untrusted Platforms: A Survey

With ever-growing data and the need for developing powerful machine lear...