Announcements¶
May 22 Final Exam Date & Info About Extra Credit
HW6 will be posted Friday 27 May. It will be an extra credit assignment due Tuesday 31 May @ 23:59 PST. The material on this homework will appear on the final exam, so even if you do not do the hw for extra credit, you are responsible for understanding it since it will be fair game for the final.
The final exam will be posted Friday 3 June @ 8:00 PST. It will be a take home exam just like the midterm. The final will be comprehensive and cover the material from all modules. This includes homework exercises and Python/Section exercises. The final exam will include both numerical exercises in Python and handwritten exercises like the midterm. As we have promised, if you do better on the final than the midterm, we will replace your midterm score with the final exam score.
Info
Practice scanning and uploading your exam in a legible format. Also practice printing your Python notebook to a pdf. Google this to see the many posts about how you can do this. We will not grade your exam if it is not legible.
May 08 HW 4 & Lectures this week
Homework 4 has been posted. This week we will continue our discussion of spectral methods. Monday we will discuss PCA and its connections to SVD and low rank approximation. Wednesday we will talk about PCR (principal component regression), KernelPCA and potentially spectral clustering depending on time. The week of 2022-05-16 we will start Module 4 on convexity and that will be the last module.
May 04 Mod2-N3 Posted
The Mod2-N3 notebook on least squares classification with MNIST has been posted.
Calendar¶
Note¶
For all dates in the future from the time you are reading this, the schedule below is only a rough outline, and is subject to change. We need to be flexible with the timing for different modules as it may take longer than expected to get through them.
| Topic | Notebooks | homework | ||
|---|---|---|---|---|
| Week 1 | ||||
| Mon 03/28 | MOD1-L1 Mod 1: Linear Algebra I resources: M1L1-RV, M1-L1 template | |||
| Released HW0 Due 11:59pm Linear Algebra Prelims | ||||
| Wed 03/30 | MOD1-L2 Mod 1: Linear Algebra II resources: M1L2-RV, M1-L2 template | |||
| Released M1-N1 Due 11:59pm K-means Clustering (Due 4/10 23:59) | ||||
| Fri 04/01 | SEC 01 M1: Linear Algebra Review resources: recorded sec, self-grade guide, python notebook | |||
| Week 2 | ||||
| Mon 04/04 | MOD1-L3 Mod 1: Linear Algebra III resources: M1L3-RV, M1-L3 template | |||
| Released HW1 Due 11:59pm Linear Algebra (Due 4/10 23:59) | ||||
| Wed 04/06 | MOD1-L4 Mod 1: Linear Algebra IV resources: M1L4-RV, M1-L4 template | |||
| Fri 04/08 | SEC 02 M1: k-means & LA review resources: recorded sec | |||
| Week 3 | ||||
| Mon 04/11 | MOD1-L5 Mod 1: Linear Algebra V resources: M1L5-RV, M1-L5 template | |||
| Released M2-N1 Due 11:59pm Least Squares System Identification (Due 4/17 23:59) | Released HW2 Due 11:59pm Linear Algebra II (Due 4/17 23:59) | |||
| Wed 04/13 | MOD2-L1 Least Squares Problem resources: M2L1-RV, M2L1 template, M2L1 temp w/ notes, M2L1-python | |||
| Fri 04/15 | SEC 03 M1/M2: LA review & Intro to Least Squares resources: python notebook (M2-N1), recorded sec | |||
| Week 4 | ||||
| Mon 04/18 | MOD2-L2 Data Fitting resources: M2L2-RV, M2L2 template, M2L2 temp w/ notes, M2L2-python | |||
| Released M2-N2 Due 11:59pm Data Fitting w/ Polynomials (Due 4/24 23:59) | Released HW3 Due 11:59pm Least Squares & Data Fitting (Due 4/24 23:59) | |||
| Wed 04/20 | MOD2-L3 Least Squares Classification resources: M2L3-RV, M2L3 template, M2L3 temp w/ notes, M2L3-python | |||
| Fri 04/22 | SEC 04 M2: Data Fitting resources: python notebook (M2-N2), recorded sec | |||
| Week 5 | ||||
| Mon 04/25 | MOD2-L4 Multi-Class Classification & Kernel Regression resources: M2L4-RV, M2-L4-template, M2L4 temp w/ notes, M2L4-python | |||
| Wed 04/27 | Review Midterm Review resources: Video, Mod1 review, Mod2 review | |||
| Fri 04/29 | EXAM Midterm Exam: Take Home | |||
| Week 6 | ||||
| Mon 05/02 | MOD3-L1 Spectral Decomposition resources: M3L1-RV, M3L1-template, M3L1 temp w/ notes, M3L1-python, M3L1-python-data | |||
| Released M2-N3 Due 11:59pm Least Squares Classification (Due 5/11 23:59) | ||||
| Wed 05/04 | MOD3-L2 SVD & Low Rank Approximation resources: M3L2-RV, M3L2-template, M3L2-supplement, M3L1-python, M3L1-python-data | |||
| Fri 05/06 | SEC 05 M2: Least Squares Classification MNIST resources: python notebook (M2-N3), recorded sec worksheet: solutions | |||
| Week 7 | ||||
| Mon 05/09 | MOD3-L3 Principle Component Analysis resources: M3L3-RV, M3L3 template, M3L3 temp w/notes, M3L3-python | |||
| Released HW4 Due 11:59pm Spectral Methods (Due 5/15 23:59) | ||||
| Wed 05/11 | MOD3-L4 PCR & Kernel PCA resources: M3L4-RV, M3L4-python, M3L4 temp w/ notes, M3L4 template | |||
| Released M3-N1 Due 11:59pm PCA for Visualizing Classification (Due 5/18 23:59) | ||||
| Fri 05/13 | SEC 06 M3: PCA resources: python notebook (M3-N1), recorded sec | |||
| Week 8 | ||||
| Mon 05/16 | MOD4-L1 Convexity & Convex Sets resources: M4L1 temp w/ notes, M4L1 template, M4L1-RV | |||
| Wed 05/18 | MOD4-L2 Convex Functions, Unconstrained Minimization, & Gradient Descent resources: M4L2 temp w/ notes, M4L2-template, M4L2-RV | |||
| Fri 05/20 | SEC 07 Convex Sets & Functions & Gradient Descent resources: python notebook (M4-N1), recorded sec | |||
| Week 9 | ||||
| Mon 05/23 | MOD4-L3 Convex Opt: ML Models I resources: M4L3-template, M4L3-RV | |||
| Released HW5 Due 11:59pm Convexity (Due 5/29 23:59) | ||||
| Wed 05/25 | MOD4-L4 Convex Opt: ML Models II resources: M4L4-template, M4L4-RV | |||
| Released M4-N2 Due 11:59pm Logistic Regression (Due 6/1 23:59) | ||||
| Fri 05/27 | SEC 08 Convex Modeling w/ Applications to ML | |||
| Released HW6 Due 11:59pm Convexity (Due 5/31 23:59) | ||||
| Week 10 | ||||
| Mon 05/30 | Holiday Memorial Day [No Class] | |||
| Wed 06/01 | Review Final Exam Review resources: annotated slides | |||
| Fri 06/03 | EXAM Final Exam: Take Home | |||