Lecture is on Mon. and Wed. (08/24/2016 to 12/08/2016) from 3PM - 4:45PM at - OLS120
The lecture schedule below is tentative and is continually subject to change; We will move at whatever pace we find comfortable.
| Index | Date | Lectures | References | Notes |
|---|---|---|---|---|
| L1 | Wed - Aug. 24 | Lecture 1 | minimum-test | Introduction/Logistics |
| L2 | Mon - Aug. 29 | Lecture 2 | Handout; (HW1 out) |
Linear Algebra Review |
| SECTION I: Supervised Regression | ||||
| L3 | Wed - Aug. 31 | Lecture 3 | Linear Regression / Normal Equation | |
| L4 | Mon - Sept. 5 | Lecture 4 | . | Optimization for Learning Linear Regression Model; |
| L5 | Wed - Sept. 7 | Lecture 4 | Optimization for Learning Linear Regression Model; | |
| L6 | Mon - Sept. 12 | Lecture 5 | HW1 due ; | Nonlinear Prediction; Local Linear Prediction; |
| L7 | Wed - Sept. 14 | Lecture 6 | HW2 out ; | Linear Prediction with Regularization, Ridge, LASSO; |
| L8 | Mon - Sept. 19 | Lecture 7 | Feature Selection | |
| L9 | Wed - Sept. 21 | Lecture 8 | HW2 due ; | Optimization for linear regression with regularization |
| L10 | Mon - Sept. 26 | Lecture 9 | Review of Regression | |
| SECTION II: Supervised Classification | ||||
| L11 | Wed - Sept. 28 | Lecture 10 Handout |
Support Vector Machine (SVM) | |
| R | Mon - Oct. 3 | READING DAY | HW3 out; HW4 out; | . |
| L12 | Wed - Oct. 5 | Lecture 10 Handout |
. | Support Vector Machine (SVM) - Pratical guide of using SVM |
| L13 | Mon - Oct. 10 | Lecture 10 Handout |
Support Vector Machine (SVM) - Extra: Dual Form | |
| L14 | Wed - Oct. 12 | Lecture 10 Handout | Support Vector Machine (SVM) - Kernel Trick | |
| L15 | Mon - Oct. 17 | Lecture 11 | HW3 due; | Probability Review |
| L15 | Wed - Oct. 19 | Lecture 12 | Generative Bayes Classifiers | |
| L16 | Mon - Oct. 24 | Lecture 12 | HW4 due; | Naive Bayes Classifier |
| L17 | Wed - Oct. 26 | Midterm | ||
| L18 | Mon - Oct. 31 | Lecture 13 Handout for MLE |
HW5 out; | Two NBC for text classification |
| L19 | Wed - Nov. 2 | Lecture 14 | Empirical Prediction Error / Discriminative vs. Generative / | |
| L20 | Mon - Nov. 7 | Lecture 15 | KNN / Bias-Variance Tradeoff / | |
| L21 | Wed - Nov. 9 | Lecture 16 | Decision Tree / Ensemble | |
| L22 | Mon - Nov. 14 | Lecture 17 | HW5 due; | Neural Network / Deep Learning / Backprop / |
| SECTION III: Unsupervised Learning | ||||
| L23 | Wed - Nov. 16 | Lecture 18 | HW6 out ; HW7 out | PCA and EigenFace for Image-based Face Recognition |
| EL24 | Fri - Nov. 18 | Lecture 17 | @OSL120 / By TA: Jack Lanchantin/ 5pm / Extra session: deep learning | |
| L25 | Mon - Nov. 21 | Lecture 19 | Hierarchical clustering / K-means Clustering / | |
| R | Wed - Nov. 23 | Thanksgiving Holiday | . | |
| L26 | Mon - Nov. 28 | Lecture 20 Lecture 21 - Extra EM |
. | GMM-EM |
| L27 | Wed - Nov. 30 | Lecture 22 | Review | |
| EL28 | Fri - Dec. 2 | @OSL120 / 3:30pm-5:30pm | Review of HW7 / By TA: Muthuraman Chidambaram | |
| E | Mon - Dec. 5 | Final In Class | HW7 due@ Dec5; HW6 due @ Dec12 ; CourseEvaluation due @ Dec7 |
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