Course pages 2019–20
Data Science: principles and practice
Lecture Slides
Lecture 1 - Introduction
Lecture 2 - Linear Regression
Lecture 3 - Classification
Lecture 4 - Ensemble Learning
Lecture 5 - Visualization
Lecture 6 - Embedding
Lecture 7 - Neural Networks, Overfitting,
Lecture 7 notes
Lecture 8 - TensorFlow, Significance Testing, Ethics,
Lecture 8 notes
Lecture 9 - Probabilistic machine learning
Practicals and code snippets
Other resources can be found on Moodle