Introduction to Week 4
A short introduction to Week 4 of the course Experimental design for machine learning - trusting results
Welcome to Week 4 of the course.
By now, we’ve been touched on all the key steps needed to produce a working machine learning model, and the data it is trained and tested upon. So what now? Can we trust our results? What do our results mean? And how can we improve them?
We will address each of these questions in turn in the following video steps:
- trusting results – how well do our results generalise?
- interpreting output – what exactly do our results show?
- improving results – can we improve our model?
We will kick things off in the next step with the video on trusting results.
Week 4 learning outcome
- Interpret and evaluate results from machine learning and deep learning models and discuss ethical considerations surrounding their use
This article is from the online course:
Experimental Design for Machine Learning
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