This is a compendium of course notes from my time at Stanford. Still under construction.
These contain some typos, since I mostly took these notes live in lecture. All errors (typographical or conceptual) are my own.
- Arch. Glorious distro.
adi.sty
. I wrote a small LaTeX style file that includes common macros / typesetting configuration that I use often.latexmk
: A perl script that provides auto-compilation on save for LaTeX documents.vim
: The best editor. I use macros / registers to input repeated snippets of LaTeX code: e.g.\sum_{n=1}^{\infty}
or\int_{0}^{\infty} f(t) e^{-st} dt
.vim-latex
: Vim package with smart braces, "jump" functionality for environments, and 1-2 character macros for most symbols (e.g.<Leader>a
outputs\alpha
in the source file).zathura
: Lightweight document viewer withvim
-like keybindings.inkscape-figures
: This is more recent, but I've found that this package makes it very easy to produce vector graphics using Inkscape (as opposed topgf
/TikZ
).exam-sheet
: Using @jcreus'sxelatex
template to create dense review sheets for exams. Requires miniature phonebook fonts (bell.ttf
, etc.) (More documentation forthcoming. For instance, see the review sheet forCS110
).tmux
Terminal multiplexer, with panes split forvim
,latexmk
,zathura
.i3wm
: Linux window manager, used for quick tiling / focus ontmux
/zathura
.stats.hs
: A short Haskell program to compute number of lines of TeX produced so far (I'd like to expand on this when I have time).
Here is a list of courses that are represented in this repo. Some of the earlier courses have less detailed notes (as early on college I hadn't perfected my workflow).
- CS43: Functional Programming Paradigms. (Notes forthcoming, offered in Winter 2020 quarter). Lectures: Isaac Schienfeld and Adithya Ganesh.
- EE376A / MATH DRP: Information Theory. Lectures: Tsachy Weissman. DRP discussions: Yuval Wigderson.
- CS273B: Deep Learning for Genomics (todo: need to add). Lectures: Anshul Kundaje.
- CS229: Machine Learning (todo: need to add). Lectures: Andrew Ng and John Duchi.
- CS279: Computational Biology. Lectures: Ron Dror.
- CS236: Deep Generative Models. Lectures: Aditya Grover and Stefano Ermon.
- CS161: Algorithms.
- CS107: Systems I. Lectures: Jerry Cain.
- CS109: Probability. Lectures: Mehran Sahami.
- CS110: Systems II. Lectures: Jerry Cain.
- MATH53: Ordinary Differential Equations. Lectures: Andrea Ottolini.
- MATH104: Applied Matrix Theory. Lectures: Katerina Velcheva.
- MATH113: (Theoretical) Matrix Theory. Lectures: Michael Kemeny.
- MATH116: Complex Analysis. Lectures: Thomas Church.
- MATH120: Group Theory. Lectures: Thomas Church.
- MATH171: Real Analysis. Lectures: George Schaeffer.
- POLISCI 101Z: Introduction to International Relations. Lectures: Mike Tomz. Discussions: Iris Malone.
- Independent Study: Statistical learning.