An introduction to machine learning (11:57)

This video lesson will give you an understanding of:

• The fundamental concepts of machine learning and how it differs from traditional statistics.

• The key distinctions between supervised and unsupervised learning, along with common algorithms like decision trees and K-means clustering.

• The role of neural networks and the importance of addressing imbalanced data and model explainability.

By the end of this video lesson, you will:

• Understand how machine learning models learn from data to make predictions or find hidden patterns.

• Be able to identify appropriate healthcare use cases for supervised and unsupervised learning.

• Recognise the challenges of imbalanced data and the need for transparent models.

For a transcript of this video lesson, click ‘download handout’ above. Once you have completed the bite-sized video, please ensure you fill out our feedback survey which can be found at the end of the course page.