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Machine Learning and Adaptive Intelligence

Welcome to the course Machine Learning and Adaptive Intelligence. This course was originally delivered at the University of Sheffield (2011-2015), but the material has been updated to make it available as a resource for students wanting to satisfy prerequisites for other courses.

Lectures

Week 1: Probability and an Introduction to Jupyter, Python and Pandas

Lecturer: Neil D. Lawrence

Week 2: Objective Functions: A Simple Example with Matrix Factorisation

Lecturer: Neil D. Lawrence

Week 3: Linear Algebra and Linear Regression

Lecturer: Neil D. Lawrence

Week 4: Data and Machine Learning Systems

Lecturer: Eric Meissner, Andrei Paleyes, Neil D. Lawrence
Time: null

Week 5: Basis Functions

Lecturer: Neil D. Lawrence
Time: null

Week 6: Generalization: Model Validation

Lecturer: Neil D. Lawrence

Week 7: Bayesian Regression

Lecturer: Neil D. Lawrence

Week 8: Dimensionality Reduction: Latent Variable Modelling

Lecturer: Neil D. Lawrence

Week 9: Probabilistic Classification: Naive Bayes

Lecturer: Neil D. Lawrence

Week 10: Logistic Regression and GLMs

Lecturer: Neil D. Lawrence

Week 11: Special Topics: Gaussian Processes

Lecturer: Neil D. Lawrence
Time: null

Special Topic Lectures

The course is designed to end with special topic lectures that build on the material but be given as guest lectures or advaned topics.