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Quality and validation of machine learning methods

Not all machine learning methods are created equal and not all training datasets are of the same standard of quality.In this project we'll look at how machine learning methods can be quality assured and validated with a particular focus on training datasets.

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Explainability of machine learning methods

Machine learning can be very powerful but its black box reputation can be an obstacle for industry.In this project we'll look at creative ways to visually convey how methods like deep neural nets, random forest, XGBoost algoritms, and support vector machines work for different audiences.

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Taxonomy of data science methods

To reap the benefits of data science it's necessary to be able to pair real world data problems with data science methods.In this project we'll begin to map out the key methods, their benefits and drawbacks, and suitability of each given some initial problem statements.

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

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