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.. title: Books
.. slug: books
.. date: 2020-09-30 21:42:32 UTC+02:00
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Here is a list of technical books that I find useful or like in
particular.
* Maths
:PROPERTIES:
:CUSTOM_ID: maths
:END:
** General maths books
:PROPERTIES:
:CUSTOM_ID: general-maths-books
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- Alexander, A: Infinitesimal: How a Dangerous Mathematical Theory
Shaped the Modern World
- Borrelli, Rullière:
[[http://math.univ-lyon1.fr/~borrelli/Kakeya.html][En cheminant avec
Kakeya]] on [[https://en.wikipedia.org/wiki/Kakeya_set][Kakeya's
needle problem]].
- Bressoud, D.M.: A Radical Approach to Lebesgue's Theory of Integration
- Bressoud, D.M.: A Radical Approach to Real Analysis
- Bressoud, D.M.: Second Year Calculus: from Celestial Mechanics to
Special Relativity
- Courant, R: What is mathematics
- Dunham, W., Euler the master of us all
- Dunham, W., The calculus galery
- Jeevanjee, N, An introduction to tensors & group theory
- Korner, T: Fourier theory
- Needham T: Visual complex analysis
- Peitgen et al, Chaos
- Vilenkin N.Ya, In search of infinity.
** Markov theory
:PROPERTIES:
:CUSTOM_ID: markov-theory
:END:
These are some great (and sometime intuitive) books to Markov chains,
martingales and optimal stopping.
- Benaïm M. and El Karoui N: Promenade aléatoire: Chaînes de Markov et
simulations : martingales et stratégie
- Dynkin E.B. and Yushkevich A.A: Markov processes: theorems and
problems
- Laurie Snell J. and Doyle P.:
[[https://math.dartmouth.edu/~doyle/][Random walks and electric
networks]]
- Kemeny and Laurie Snell: Finite Markov Chains.
- Norris J: Markov chains
- [[https://arxiv.org/abs/1209.3632][Baez J.C. and Biamonte J: Quantum
Techniques for Stochastic Mechanics]]
- Stachurski J: [[https://johnstachurski.net/edtc][Economic Dynamics:
Theory and Computation]]
** Physics
:PROPERTIES:
:CUSTOM_ID: physics
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- Gourgoulhon E., Relativite restreint des particules a l'astrophysique.
A good book to prepare yourself for general relativity. It covers all
I learned as a student on special relativity, and more.
- Zee A.: Einstein Gravity in a Nutshell
- Flanders H.: Differential forms with applications to the physical
sciences
- Nahin, P.J.: Hot Molecules, Cold Electrons: From the Mathematics of
Heat to the Development of the Trans-Atlantic Telegraph (2020) (It is
a petty that Nahin appears not to have read the book of Korner on
Fourier theory. There is a lot of overlap, and I like Korner' account
better.)
- Nahin, P.J.: In Praise of Simple Physics: The Science and Mathematics
behind Everyday Questions
** Probability
- Lindley, D.V.: Understanding Uncertainty, A really nice book to help
how to think about probability.
- [[https://www.cambridge.org/gb/academic/subjects/physics/theoretical-physics-and-mathematical-physics/probability-theory-logic-science][Jaynes E.T]] Probability theory: the logic of science. I like his opinionated writing a lot. It's funny at times, but often very to the point.
- Diaconis, P and Skyrms, B: Ten Great Ideas about Chance, Also an
interesting book that discusses general probability concepts.
- [[https://math.dartmouth.edu/~prob/prob/prob.pdf][Grinstead and Laurie
snell, introduction to probability]].
- Capinski M., Tomasz Jerzy Zastawniak: Probability Through Problems.
Targeted at students that like to learn a bit of measure theory.
- Ash, R. B., Real analysis and probability, if you like something
tougher.
** Queueing theory
- [[https://github.com/ndvanforeest/queueing_book][Van Foreest, N.D., Analysis of Queueing Systems with Sample Paths and Simulation]], which is free, and contains lots of problems and solutions.
- Tijms, H.C: A First Course in Stochastic Models, Wiley, 2003.
* Programming
** lisp
- [[https://norvig.github.io/paip-lisp/#/][Norvig, P: Paradigms of Artificial Intelligence Programming]]
- Domkin, V.: Programming Algorithms in Lisp: Writing Efficient Programs with Examples in ANSI Common Lisp
- [[http://xahlee.info/emacs/emacs/elisp_examples.html][Lee X: Emacs Lisp: Simple Emacs Lisp Examples]]
** Algorithms
- Cormen, T.H. et al: Introduction to Algorithms
- Hetland, M.L.: Python Algorithms, Mastering Basic Algorithms in the
Python Language
- Kopec, D.: Classic Computer Science Problems in Python
** Think books
Here are some books freely available for [[http://greenteapress.com/wp/][download]].
I encourage you to browse through all of these books.
The reason I recommend these books is that they combine three enormously important skills for students with a penchant for quantitative work: 1.
Making and adapting (mathematical) models; 1.
Analyzing (quantitatively) the models with computers; 1.
Evaluating and interpreting the results.
The books are:
- Think Stats
- Probability and statistics for programmers
- Think Bayes
- Modeling and Simulation in Python
- Think Complexity.
- How to think like a computer scientist
* General
** Operations management
:PROPERTIES:
:CUSTOM_ID: operations-management
:END:
- Goldratt, E.M.: The goal
- Womack, J.P. and Jones, D.T.: The Machine That Changed the World: The
Story of Lean Production-- Toyota's Secret Weapon in the Global Car
Wars That Is Now Revolutionizing World Industr