acganesh / compendium

Stanford course notes in math / CS

stanford-compendium

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.

Workflow

• 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 with vim-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 to pgf / TikZ).
• exam-sheet: Using @jcreus's xelatex template to create dense review sheets for exams. Requires miniature phonebook fonts (bell.ttf, etc.) (More documentation forthcoming. For instance, see the review sheet for CS110).
• tmux Terminal multiplexer, with panes split for vim, latexmk, zathura.
• i3wm: Linux window manager, used for quick tiling / focus on tmux / 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).

Course list

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.