| Date |
Lecture |
Slides |
Useful links |
HWs |
|
|
|
|
|
|
| August 31 Monday |
Intro to ML concepts |
Lecture1.pdf |
Murphy: Sec 1.1-1.3 |
|
| September 2 Wednesday |
Intro to ML concepts |
Intro_contd.pdf, Lecture2_inked.pdf |
|
QnA 1 out |
| September 7 Monday |
Labor Day -- No class |
|
|
|
| September 9 Wednesday |
MLE, Bayes classifier |
MLE_BayesClassification.pdf, Lecture3_inked.pdf |
Bishop: Sec 2.1-2.3.6, 1.5, Mitchell_Ch |
QnA1 due, HW1 out |
| September 14 Monday |
MLE, decision boundary |
Lecture4_inked.pdf |
|
|
| September 16 Wednesday |
MAP, Naive Bayes |
NaiveBayes_MAP.pdf, Lecture5_inked.pdf |
Mitchell_Ch (Secs 1-2) |
|
| September 21 Monday |
Logistic Regression |
LogisticRegression.pdf, Lecture6_inked.pdf |
Mitchell_Ch (Secs 3-5), On Discriminative and Generative Classifiers, Ng and Jordan, NIPS, 2001 (pdf) |
|
| September 23 Wednesday |
Linear regression |
Lecture7_inked.pdf, LinearReg.pdf, Lecture8_inked.pdf |
Murphy: Sec 7.1-7.3 |
HW1 due, QnA2 out (Fri Sept 25) |
| September 28 Monday |
Regularization, Nonlinear regression |
LinearNonLinReg.pdf, Lecture9_inked.pdf |
Murphy: Sec 7.5-7.6 |
|
| September 30 Wednesday |
Neural networks |
Lecture9contd_inked.pdf, NeuralNets.pdf |
Goodfellow et al: Ch 6 |
QnA2 due, HW2 out (Fri Oct 2) |
| October 5 Monday |
Neural Networks |
Lecture10_inked.pdf |
Goodfellow et al: Ch 6 |
|
| October 7 Wednesday |
Deep Convolutional Neural Networks |
CNN.pdf, Lecture11_inked.pdf, NNTipsTricks.pdf |
Bishop: Sec 2.5, Goodfellow et al: Ch 9 |
|
| October 12 Monday |
Nonparametric methods - density estimation, kernel regression, Nearest neighbors |
nonparametric.pdf |
Bishop: Sec 2.5, Notes Eduardo, Murphy: Sec 1.4 |
|
| October 14 Wednesday |
Mid-term review |
Lecture13_inked.pdf, MidtermReview.pdf |
|
HW2 due, QnA3 out (Thurs Oct 15) |
| October 19 Monday |
Midterm Quiz (in-class) |
|
|
|
| October 21 Wednesday |
Support Vector Machines (hard, soft) |
SVM.pdf, Lecture14_inked.pdf |
Bishop: Sec 7.1.1-7.1.3, Sec 4.1.1, 4.1.2, Appendix E |
QnA3 due, HW3 out |
| October 26 Monday |
Support Vector Machines (dual) |
SVM_dual.pdf, Lecture15_inked.pdf |
Bishop: Sec 7.1.1-7.1.3, Sec 4.1.1, 4.1.2, Appendix E |
|
| October 28 Wednesday |
Support Vector Machines (kernel trick) |
svm_dual_kernel.pdf, Lecture16_inked.pdf |
Bishop: Sec 6.1, 6.2, SVMdemo |
|
| November 2 Monday |
Kernelized Logistic and Linear Regression |
Kernels_contd, Lecture17_inked.pdf
|
Slides 52-56 KRR Dual derivation, Welling's KRR Notes.pdf |
|
| November 4 Wednesday |
Decision Trees |
DecisionTrees, Lecture18_inked.pdf |
Mitchell: Ch 3 |
HW3 due, QnA4 out |
| November 9 Monday |
Boosting |
Boosting.pdf, Lecture19_inked.pdf |
Bishop: Sec 14.3
Schapire: Boosting Tutorial, Video |
|
| November 11 Wednesday |
Model selection, cross-validation |
ModelSel.pdf, Lecture20_inked.pdf |
Bishop: Sec 1.3, 3.2 |
QnA4 due, HW4 out |
| November 16 Monday |
Dimensionality Reduction |
Dim_Red.pdf, Lecture21_inked.pdf |
Bishop Ch. 12 through 12.1 |
|
| November 18 Wednesday |
Clustering, Mixture models |
clusteringGMM.pdf, Lecture22_inked.pdf |
Bishop: Sec 9.1,9.2 |
|
| November 23 Monday |
Expectation-Maximization |
EM.pdf, Lecture23_inked.pdf |
Bishop: Sec 9.1,9.2 |
|
| November 25 Wednesday |
Thanksgiving -- No class |
|
|
HW4 due |
| November 30 Monday |
Learning Theory (PAC bounds) |
theory.pdf, Lecture24_inked.pdf |
Mitchell: Ch 7, Murphy: Sec 6.5.4 |
QnA5 out |
| December 2 Wednesday |
Leaning Theory (VC dimension) |
theoryII.pdf, Lecture25_inked.pdf |
Mitchell: Ch 7 |
|
| December 7 Monday |
Exam Review |
FinalReview_inked.pdf |
Practice Problems on Piazza |
QnA5 due |
| December 9 Wednesday |
Final Quiz (in-class) |
|
|
|
