dc.contributor.author | Getuno, Daniel Makini | |
dc.contributor.author | Hadullo, Kennedy Ochilo | |
dc.date.accessioned | 2024-03-01T07:01:17Z | |
dc.date.available | 2024-03-01T07:01:17Z | |
dc.date.issued | 2021-06-04 | |
dc.identifier.citation | Hadullo, K.O., & Getuno, D.M. (2021). Machine Learning Software Architecture and Model Workflow. A Case of Django REST Framework. | en_US |
dc.identifier.uri | http://ir.tum.ac.ke/handle/123456789/17512 | |
dc.description | DOI: 10.3844/ajassp.2021.152.164 | en_US |
dc.description.abstract | The purpose of this study was to find out the challenges facing
Machine Learning (ML) software development and create a design
architecture and a workflow for successful deployment. Despite the promise
in ML technology, more than 80% of ML software projects never make it to
production. As a result, majority of companies around the world with
investments in ML software are making significant losses. Current studies show
that data scientists and software engineers are concerned by the challenges
involved in these systems such as: Limited qualified and experienced ML
software experts, lack of collaboration between experts from the two
domains, lack of published literature in ML software development using
established platforms such as Django Rest Framework, as well as
existence of cloud software tools that are difficult use. Several attempts
have been made to address these issues such as: Coming up with new
software models and architectures, frameworks and design patterns.
However, with the lack of a clear breakthrough in overcoming the
challenges, this study proposes to investigate further into the conundrum
with the view of proposing an ML software design architecture and a
development workflow. In the end, the study gives a conclusion on how
the remedies provided helps to meet the objectives of study. | en_US |
dc.description.sponsorship | Technical University of Mombasa | en_US |
dc.language.iso | en | en_US |
dc.publisher | American Journal of Applied Sciences | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Data Science | en_US |
dc.subject | Software Engineering | en_US |
dc.subject | Development | en_US |
dc.subject | Deployment | en_US |
dc.subject | Django REST Framework | en_US |
dc.subject | Architecture | en_US |
dc.subject | Workflow | en_US |
dc.title | Machine Learning Software Architecture and Model Workflow. A Case of Django REST Framework | en_US |
dc.type | Article | en_US |