1:25-3:10 MW, MCG 1304
Dr. Rashid’s office hours: M (after class)
Grader office hours: M 4-5, MCG 1305
For Rmd
files, go to the course repo
and navigate the directories, or best of all to clone the repo and
navigate within RStudio.
Week | Topic | Dir. | HW | HTML | Title |
---|---|---|---|---|---|
Module 1 | Sci. research | ||||
Jan 10 | R code | rpkg |
hw | efficient | Readable and efficient R code |
Jan 17 | R package | rpkg |
hw | build | Building an R package |
document | Documenting an R package | ||||
test | Writing package tests | ||||
debug | Debugging in R | ||||
Jan 22 | C++ from R | rpkg |
hw | rcpp | Calling C++ with Rcpp |
Jan 24, 29 | Large data | large |
hw | datatable | Working with data.table |
sqlite | Working with RSQLite |
||||
hdf5 | Working with rhdf5 |
||||
sparse | Sparse data manipulation | ||||
Module 2 | Optim. & Num. int. | ||||
Feb 31, 5, 7 | General optim. | optim |
hw | optim | General optimization |
Feb 12, 14 | EM algorithm | em |
hw | em | EM algorithm |
Feb 19, 21 | Numer. integration | numint |
hw | numint | Numerical integration |
Feb 26, 28, Mar 4 | General MCMC | mcmc |
hw hw2 | mcmc | General MCMC |
Mar 6, 18 | Advanced MCMC | advmcmc |
hw | advmcmc | Advanced MCMC |
Module 3 | Mach. learning | ||||
Mar 20, 25, 27 | ML essentials | ml |
hw | essentials | Machine learning essentials |
Apr 1, 3 | SVM, RF | ml |
hw | svm | Support vector machines |
rf | Random forests | ||||
Apr 8, 9 | NN, Guest Lecture | ml |
nn | Neural networks | |
Apr 11,16,18 | Projects | ||||
Apr 22, 24, 29 | Wrap-up |
This page was last updated on 01/10/2024.