Machine learning approaches: linear and logistic regression, SVMs, kernel methods, random forests and ensembles

This week’s topics

Machine learning approaches: linear and logistic regression, SVMs, kernel methods, random forests and ensembles

1. Machine learning approaches: linear and logistic regression, SVMs, kernel methods, random forests and ensembles
2. The bias-variance trade-off

What you will be able to do

• 1.2 Describe a range of simple and complex machine learning strategies.
• 1.4 Analyse the significance of the bias-variance trade-off in machine learning.
• 2.2 Explain the bias-variance trade-off in machine learning.

Activity

Seminar, guided reading and a short written task: describe a range of simple and complex machine learning strategies.

Study materials