Wiki
CS B555: Machine Learning
Class schedule
This schedule is tentative and will almost definitely change throughout the semester.
Readings are from the notes: notes.pdf Download notes.pdf
These notes may change to fix any issues or typos; look at the date on the first page to see how recently they have been updated. I recommend avoiding printing anything beyond the chapter you are currently reading, as some sections may change. This is particularly true for Chapter 6-8 and the appendix.
A (very rough and still in-progress) reference for math notation: notation.pdf Download notation.pdf
| Week | Date | Lecture | Readings and Deadlines |
| 1 | Aug 22 | Introduction: Lec1-Introduction.pdf Download Lec1-Introduction.pdf |
Assignment #1 released Thought questions #1: -read Chapters 1, 2 and 3 from the notes.pdf Download notes.pdf |
| Aug 24 | Probability: Lec2-Probability.pdf Download Lec2-Probability.pdf | ||
| 2 | Aug 29 |
Probability: Lec2-Probability-2.pdf Download Lec2-Probability-2.pdf Starting Parameter Estimation: Lec4-ParameterEstimation.pdf Download Lec4-ParameterEstimation.pdf |
Office hours for AIs: 2:30 - 4:00 p.m. Tuesday 1:00 - 2:30 p.m. Wednesday Office hours for Martha: 3:00 - 5:00 p.m. Tuesday |
| Aug 31 | Parameter Estimation: Lec4-ParameterEstimation_2.pdf Download Lec4-ParameterEstimation_2.pdf | ||
| 3 | Sep 5 |
No classes: Labour day Office hours moved to Wednesday |
|
| Sep 7 |
Intro to prediction problems: Lec5-IntroML.pdf Download Lec5-IntroML.pdf |
Thought questions #1 due | |
| 4 | Sep 12 | Linear regression: Lec7-LinearRegression.pdf Download Lec7-LinearRegression.pdf | |
| Sep 14 |
Linear regression:Lec7-PracticalLinearRegression.pdf Download Lec7-PracticalLinearRegression.pdf Matlab demo: example11.m Download example11.m |
Assignment #1 due Assignment #2 released |
|
| 5 | Sep 19 |
Regularization: Lec8-Regularization.pdf Download Lec8-Regularization.pdf |
|
| Sep 21 | Optimization: Lec9-StochasticOptimization.pdf Download Lec9-StochasticOptimization.pdf | ||
| 6 | Sep 26 | Generalized Linear Models: Lec10-GLMs.pdf Download Lec10-GLMs.pdf | |
| Sep 28 |
Generalized Linear Models and logistic regression: Lec11-LogisticRegression.pdf Download Lec11-LogisticRegression.pdf Matlab demo: logistic regression and linear regression, logistic.zip Download logistic.zip |
Thought questions #2 due | |
| 7 | Oct 3 | Naive Bayes: Lec12-NaiveBayes.pdf Download Lec12-NaiveBayes.pdf | |
| Oct 5 |
Multiclass classification: Lec13-Multiclass.pdf Download Lec13-Multiclass.pdf In-class questions: feedback.pdf Download feedback.pdf |
|
|
| 8 | Oct 10 |
Multiclass Classification: Lec14-Multiclass2.pdf Download Lec14-Multiclass2.pdf |
|
| Oct 12 |
Multiclass Classification (cont): Lec14-Multiclass2.pdf Download Lec14-Multiclass2.pdf |
Assignment #2 due Assignment #3 released |
|
| 9 | Oct 17 | SVMs: Lec15-SVMs.pdf Download Lec15-SVMs.pdf | |
| Oct 19 | Review: Lec16-Review.pdf Download Lec16-Review.pdf | Thought questions #3 due | |
| 10 | Oct 24 | Fixed representations for learning nonlinear functions: Lec17-Representations.pdf Download Lec17-Representations.pdf | |
| Oct 26 | Fixed representations (continued...): Lec18-Representations2.pdf Download Lec18-Representations2.pdf | ||
| 11 | Oct 31 | Neural networks: Lec19-NeuralNetworks.pdf Download Lec19-NeuralNetworks.pdf | |
| Nov 2 | Neural networks (cont...): Lec20-NeuralNetworks2.pdf Download Lec20-NeuralNetworks2.pdf | Quiz #1: Chapters 1-4 | |
| 12 | Nov 7 | Factorization and unsupervised learning: Lec21-Factorization.pdf Download Lec21-Factorization.pdf | |
| Nov 9 |
Semi-supervised learning, missing data and hidden variable models: Lec22-MissingVariables.pdf Download Lec22-MissingVariables.pdf
|
||
| 13 | Nov 14 |
Hidden variable models and Bayesian regression: Lec23-HiddenVariables.pdf Download Lec23-HiddenVariables.pdf EM demo: em.zip Download em.zip |
|
| Nov 16 | Boosting and ensembles: Lec24-Ensembles.pdf Download Lec24-Ensembles.pdf |
Assignment #3 due Assignment #4 released |
|
| 14 | Nov 21 | No classes: Thanksgiving | |
| Nov 23 | No classes: Thanksgiving |
|
|
| 15 | Nov 28 |
Performance measures and evaluation: Lec27-EvaluationAndErrorFunctions.pdf Download Lec27-EvaluationAndErrorFunctions.pdf Office hours for Martha: 5:30 p.m. - 7:00 p.m. on Monday |
|
| Nov 30 | Guest lecture: Prof. Donald Williamson | Quiz #2: Chapters 5-7 | |
| 16 | Dec 5 |
No class No office hours for Martha, but office hours for AIs remain the same |
|
| Dec 7 |
No class |
Assignment #4 due |
|
| 17 | Dec 14 |
Additional review class from 4:00 p.m. to 5:15 p.m. in Info East 150 |
|
| Dec 16 |
Final exam: 5:00 p.m. - 7:00 p.m., JHA 100 |