Principles of Machine Learning

This module will introduce learners to some of the most widely-used techniques in machine learning. The module will cover various topics in supervised and unsupervised learning, including linear regression, polynomial regression, classification with logistic regression and clustering. The module will cover both theoretical and practical aspects of machine learning, such as theoretical concepts behind linear and nonlinear regression problems and the practical implementation of logistic regression in Python. At the end of the module, learners will be able to formalise a machine learning task, choose the appropriate numerical method, implement the algorithm in Python and assess the method’s performance.

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