Description of field of research:
The demand for the application of Machine Learning (ML) has been on the rise across various industries. Machine Learning tools required to be tailored into business settings to address their requirements. This requires a data scientist expert to assess data quality, pre-process data, select suitable machine learning technique and visualising data. This can be costly and ineffective for many businesses.
AutoML is a novel technology that seeks to assist domain experts to utilise the power of ML by automating entire ML pipeline. The low-code aspect of AutoML enables faster development and higher maintainability, thus offering significant benefits to business.
The focus for this research is to examine and discover the potential opportunities that AutoML tools can provide to businesses.
School
Research Area
Machine Learning | Artificial Intelligence | ML for business | Automated Machine Learning | AutoML | ML pipeline | Software Engineering
- Research Environment
- Expected Outcomes
- Reference Material/Links
- Our team
This project will be conducted under supervision of Dr Chitizadeh.
Dr Chitizadeh is a member of the UNSW FinTech AI Innovation Consortium (FAIC) team.
The research findings will be presented in the form of a scholarly research article, which will be submitted to a reputable academic workshop or conference.
https://link.springer.com/chapter/10.1007/978-3-030-95987-6_14
https://arxiv.org/pdf/1908.00709.pdf?arxiv.org
https://link.springer.com/article/10.1007/s11831-022-09765-0
https://karmake2.github.io/files/Publications/2021/AutoML.pdf
https://learn.microsoft.com/en-us/azure/machine-learning/concept-automated-ml
