IAML-PG2: Course Materials
Syllabus
For accessing the slides and pre-recorded videos, please direct to LEARN.
Week 1
Study, do the quiz and submit questions on Piazza during week 1 - use topic:topic_data
- Introduction
- Thinking About Data
- Probability Topics
Week 2
Study, do the quiz, and submit questions on Piazza in the topic_naivebayes folder, before Wednesday week 2
Study, do the quiz, and submit questions on Piazza in the topic_dt folder, before Wednesday week 2
- Naive Bayes
- Decision Trees
Week 3
Study, do the quiz, and submit questions on Piazza in the topic_eval folder, before Wednesday week 3
- Generalisation and Evaluation
Week 4
Study, do the quiz, and submit questions on Piazza in the topic_optimisation folder, before Monday week 4
- Optimization and Regularization
Week 5
Study, do the quiz, and submit questions on Piazza in the topic_linear_regression folder, before Monday week 5
Study, do the quiz, and submit questions on Piazza in the topic_logistic_regression folder, before Wednesday week 5
- Linear Regression
- Logistic Regression
Week 6
Study, do the quiz, and submit questions on Piazza in the topic_svm folder, before Wednesday week 6
Study, do the quiz, and submit questions on Piazza in the topic_ethics folder, before Wedn esday week 6
- Support Vector Machines
- Ethics in Machine Learning
Week 7
Study, do the quiz, and submit questions on Piazza in the topic_knn folder, before Wednesday week 7
Study, do the quiz, and submit questions on Piazza in the topic_kmeans folder, before Wednesday week 7
Study, do the quiz, and submit questions on Piazza in the topic_gmm folder, before Wednesday week 7
- Nearest Neighbours
- K-Means
- Gaussian Mixture Models
Week 8
Study, do the quiz, and submit questions on Piazza in the topic_pca folder, before Wednesday week 8
Study, do the quiz, and submit questions on Piazza in the topic_hierarchical_clustering folder, before Wednesday week 8
- Principal Components Analysis
- Hierarchical Clustering
Week 9
Study during week 9
- Neural Networks
Week 10
- Revision Week
Lecture Recordings
All lecture recordings should be accessed via Learn; you will need to log in using your EASE account. (Learn provides you with access to any lecture recordings available for this course. You will need to select the "lecture recording" link once, before you can access any direct links to a lecture recording.)