This is a graduate-level proseminar.
Part II: Learning dimensions and concepts
Deliverable goals
| Week | Date | Topic | Class | HW to do | Methods bootcamp tasks |
|---|---|---|---|---|---|
| 13-14 | Tu 11/31-12/08 | GAMMs | Time series, time normalization | Try doing GAMMs for Luganda data, work on your own projects | |
| Th 10/27 | Wrap-up |
| Week | Date | Topic | Class | HW to do | Methods bootcamp tasks |
|---|
| Week | Date | Topic | Class | HW to do | Methods bootcamp tasks |
|---|---|---|---|---|---|
| 11 | Tu 11/15 | Bayesian regression, multilevel models | BDA Ch. 3, 4, 5, Gelman and Hill 2007 Chs. 11, 12 | ||
| Tu 11/17 | |||||
| 10 | Tu 11/08 | GAMMs | Gubian tutorial | Work through Gubian tutorials + apply to Luganda | |
| Th 11/10 | Residuals | More work on Luganda | Work through Van Rij et al. paper, html, git, review GHV Ch. 7, 8, do Ch 9 | ||
| 9 | Tu 10/31 | GAMMs | GAMMs for Luganda data | ||
| Th 11/02 | Gubian tutorial | Work through Gubian tutorials | |||
| 8 | Tu 10/25 | GAMMs | Wieling 2018 tutorial | Try doing GAMMs for Luganda data | (See Wood 2017 book in shared readings directory) |
| Th 10/27 | |||||
| 7 | Tu 10/18 | Temporal considerations: decomposing trajectories | Gubian tutorial materials | Work on own data, ICPhS thoughts! | Work through Wieling 2018 tutorial |
| Th 10/20 | No class: AMP travel | ||||
| 6 | Tu 10/11 | Classification/regression | ISLR2 Ch. 4 discussion | ||
| Th 10/13 | Work on own data | Work through Ross GAMs course | |||
| 5 | Tu 10/04 | MDS, what spaces methods presentations wrap-up | Morrison and Kondaurova (2009) paper, code, see also qda paper, ky code | Get stanarm etc. installed | |
| Th 10/06 | Hands-on work on data | Set up data set work | Work on own data | Work through ISLR Ch. 4, GHV Ch. (10), 11, 13 | |
| 4 | Tu 09/27 | What space cont'd | jupyter notebook | Review what space methods papers | |
| Th 09/29 | |||||
| 3 | Tu 09/20 | What space? Change of bases, subspaces: dimensionality reduction, PCA, LDA, MDS, SVMs, neural nets, linear algebra review cont'd | Alessa/Josh on transformations | ||
| Th 09/22 | KY gone at compphon workshop; Responsible adult GHV exercise session | Work on your self-assigned papers for next week | Watch the non-square matrix video (and dot product one would help too) | ||
| 2 | Tu 09/13 | Changing the graph paper: transformations and scaling -- "normalization", "centering", linear regression review | Notes | Due by 09/15: Linear regression review: perspectives-Read Appendix B and Ch. 4 of GHV, Ch. 16 of Winter (2019). Then GHV Ch. 7, 8 | |
| Th 09/15 | Pick Wk 3 method and paper(s) to present. | Due by 09/20: Linear algebra review: work through 3Blue1Brown linear algebra vids 4, (5), 6, 13, and 14 | |||
| 1 | Tu 09/06 | Introduction, linear algebra review | Spaces notes | Due by class 09/08: Work through 3Blue1Brown linear algebra vids 0, 1, 2, 3, and 16 (Supplemental: Linear algebra done right Ch. 1 and definition of vector space video) | |
| Th 09/08 | Prep your transformation topic. Pick data set to work on. | Due by 09/13: Probability review: work through 3Blue1Brown Bayes Theorem 1, Binomial distribution, pdfs. Linear regression review: work through GHV Chs 5, 6, 12 [code]. | |||
| 0 | Review: R-fu | - R basics (swirl) - tidyr basics: R for data science, especially data visualization, data transformation, EDA, , - Data wrangling: R4DS, Baert dplyr tutorials, pivoting, magittr pipe, (new native pipe??) |