math and computers and stuff

CS

228 Prob Graph Models Keller-Friedman, Probabilistic Graphical Models

- much expanded / easier version of Murphy’s sections on this
- good to undrestandg Bayesian details and go deeper!

295Q Nielsen-Chung, Quantum Computation and Quantum Information

- quantum computing mostly from CS theory/algorithmic perspective
- ok, better focus on physics I think

254 Complexity Arora-Beck, Computational Complexity

- pretty much standard complexity book, but well organized and covers some modern topics too! (circuits, coding, quantum, PCP, etc)
- complexity theory is still not really useful

Tufte other books

- good but similar to existing

CME 108 Scientific Computing Ascher-Greif, First Course in Numerical Methods

- very good! Applied but much more useful focus than other numerical analysis books
- less interpolation and derivation crap
- more numerical linear algebra, eigenvector/eigenvalue, LR/QR, convex opt, etc

Business

ACCT 313 Accounting Based Valuation McKinsey, Valuation

- overall book on analyzing businesses incl forecasting etc
- very very MBAish (dull!)
- full of generalities Wahlen et al, Financial Reporting, Financial Statement Analysis, and Valuation
- more detailed dive into finance side o accounting
- risk, profitiability, accounting premises, case studies etc
- more specific/actional but also much more textbook-ish than McKinsey
- these books go deep into accounting for finance purposes (so boring!!)

FIN 211 Corporate Finance Berk-Demarzo

FIN 305 Capital markets and investiments Bodie-Kane-Marcus

GSB 305 Investing for Good David Swansen, Pioneering Portfolio Management

- interesting! qualitative perspective on very long term institutional investment (eg university endowment)

ACCT 618 Market Efficiency and Information Arbitrage Nicola Gennaioli and Andrei Shleifer, Crises of Belief (cheap! $30)

- how information quantitatively drives investor decisions
- like Taleb appendices, but more so
- definitely find this!! (eventually)
- this is hard and more of a research monograph than a textbook

MGTECON 203 Managerial Economics Accelerated Kreps, Microecronomics for Managers (cheap! $40)

- interesting! Covers smattering of topics from Mas-Colell (fancier than eg Varian) with specific applied/biz focus. Cool!
- speifically focused on MBA needs vs grad study in econ
- I think this is perfect complement/continuation for Varian => take a look!
- dont buy (too easy) but definitely try to read it!

OIT 367 Big Data Taddy, Business Data Science (cheap! $25)

- very good, like Shalzi/other applied regression books (even includes R)
- includes regression experiments (A/B testing), confidence, basic ML incl. regularization, etc with lots of R code examples
- audience: “data scientists at data-driven firms, with nonspecialist backgrounds” – that’s me!

Economics

51 Microeconomics II Varian, etc

102B Applied Econometrics Hill et al, Principles of Econometrics

- lots of basic applied stats crap (Rice stuff)
- 2nd half covers good/standard techniques specific to time series both simple and fancier stuff (ARCH/GARCH, VEC, VAR etc)
- but this book is not very well written, maybe better to find a specific finance book on time series instead

Physics (just for fun)

63 E&M Purcell

130 Quantum Griffiths

160 Astrophysics (undergrad) Maoz, Astrophysics in a Nutshell

- actually an undergrad astrophysics book! Cool!

330 QFT Peskin-Schroeder

360 Astrophysics Carroll Rybicki, Radiative Processes in Astrophysics

362 Early Universe Kolb-Turner, The Early Universe

Math

175 Functional Analysis Young, Intro to Hilbert Space

- very short, terse, dense!
- but lively to read, lots of exercises

205B Real Analysis II Schechter, Principles of Functional Analysis

- shrink wrapped, but claims to cover Banach space, Hilbert space, operators, etc all from upper UG / easy grad level! How??

236 Stochastic Differential Equations Oksendal, Stochastic Differential Equations

- hard! Think Benedetti-Petronio book
- had better learn grad probability first
- get to this eventually…

239 Mathematical Finance Bjork, Arbitrage Theory in Continuous Time

- the real MFE stuff
- really depends on stochastic DEs but pretends in doesn’t
- more applied perspective
- this is the most readable mathematical finance book I’ve found so far (not saying much…)

EE

Too many courses stuck in shrink wrapped readers, including signals :(

364A Convex Optimization Boyd-Venderbergh, Convex Optimization

- big scary textbook, but this is/seems like the standard book!
- this is a very influential and important to understand
- get this and go through it
- this topic is more important than theoretical stats! (not applied stats)

103 Intro to Matrix Methods Boyd-Vanderberghe, Intro to Applied Linear Algebra

- 1st half of the book is very basic linear algebra, but 2nd half covers many variants on approximation / least squares!
- don’t buy but very worthwhile to know!

101A circuits Hambley, Electrical Engineering Sedra-Smith, Microelectronic Circuits

108 Digital Systems Dally-Harting, Digital Design

- how to actually build adders, shifters, floating point, FSM/microcode
- cool!!

264W Digital Signals Oppenheim-Schafer, Discrete-Time Signal Processing

- dense, dry, gory

Statistics

203 Intro to ANOVA Faraway, Linear Models w/ R

- yet another upper UG applied regression book, boring Freedman, Statistical Models
- not the same as his other book!
- really good!! Some illuminating discussion, clear focus on applied modeling, really really good examples
- GET THIS ASAP

208 Bootstrap and Cross Validation Efron, Large Scale Inference

- this guy invented bootstrap
- very advanced/research monograph stuff though not super theoretical
- read this as “advanced teaser”

290 Computing Hadley-Wachman, Advanced R

- best book I’ve ever seen on R!
- like those Schemer/Effective C++ books
- explains how the language really works, instead of cookbook

217 Stochastic Processes Pinsky-Carlin, Intro to Stochastic Models

- 1st half review but 2nd half hasgood easy UG intro to continuous time Markov, Brownian motion, etc
- simpler/more exlpicit/easier exercises than math textbook
- probably math textbook is better

221 Random Processes and Graph Lattices Grommett, Probability on Graphs

- very cool! quick hard book covering Gibbs random fields, Ising model etc

300B Theoretical Stats II Lehmann books van der Vaart, Asymptotic Statistics

- this is where that grad probability is actually used to prove stuff
- probably don’t ever need it

310B Probability II Billingsley Durrett Williamns, Probability with Martingales

- shorter/slimmer than Durrett, but no exercises and very hard

317 Stochastic Processes Karlin-Taylor, Second Course in Stochastic Processes

- sequel to that book at the library (equivalent to “easy book” above)
- starts to look cooler!