An Illustrative Guide to Multivariable and Vector Calculus

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1. dozgonOct 2022
   - Geometry (Euclidean Geometry)

   - Algebra (Linear Algebra)

   - Calculus & Analysis

   - Physics

   Many university curricula include linear algebra and vector calculus. Physics is mandatory for all engineering disciplines.

   Therefore, my suggestion would be to preserve the language of our universe and abstract thinking patterns (i.e. mathematics) and the rules of our universe (i.e., physics).

   Those 2 are the absolute minimum, I would say, to rebuild modern civilization from scratch.

   MATHEMATICS

   - Linear Algebra by Friedberg, Insel and Spence.

   - Linear Algebra Done Right by Sheldon Axler

   - Linear Algebra Done Wrong by Sergei Treil

   - An Illustrative Guide to Multivariable and Vector Calculus

   - Vector Calculus by Tromba & Marsden

   - Vector Calculus by Colley

   PHYSICS

   - Fundamentals of Physics by Jearl Walker

   - The Theoretical Mimimum by Susskind

   EXTRAS

   - Measurement by Lockhart

   - Code by Petzold

   - Structure and Interpretation of Computer Programs

   - Books by the ancient Greeks

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2. epguiDec 2021
   I spend a lot of time sniffing them out.

   One thing I'll do once in a while is visit a university bookstore to get a sense of what's being used in classrooms. I ended up with a lot of my law textbooks like that. In law, I've really loved:

   - Canadian Administrative Law (Guy Régimbald): https://store.lexisnexis.ca/en/categories/shop-by-jurisdicti...

   - Tort Law (Horsey & Rackley): https://www.amazon.ca/Tort-Law-Kirsty-Horsey-dp-019886776X/d...

   - Handbook of Canadian Higher Education Law (Shanahan, Nilso & Broshko): https://www.amazon.ca/Handbook-Canadian-Higher-Education-Law...

   I've been on a maths, stats and ML/AI binge in the last year, and so far my top picks are:

   - Calculus (Stewart): https://www.amazon.ca/Calculus-James-Stewart/dp/1337624187/

   - Linear Algebra Done Right (Sheldon Axler): https://www.amazon.ca/Linear-Algebra-Right-Undergraduate-Mat...

   - An Illustrative Guide to Multivariable and Vector Calculus (Miklavcic): https://www.amazon.ca/gp/product/3030334589/

   - Probability: A Graduate Course (Allan Gut): https://www.amazon.ca/gp/product/1461447070/

   - Statistical Rethinking (McElreath): https://www.amazon.ca/gp/product/036713991X/

   - An Introduction to Statistical Learning (James, Witten, Hastie & Tibshirani): https://www.amazon.ca/Introduction-Statistical-Learning-Appl...

   - Regression and Other Stories (Gelman, Hill & Vehtari): https://www.amazon.ca/gp/product/1107676517/

   - Data Analysis Using Regression and Multilevel/Hierarchical Models (Gelman & Hill): https://www.amazon.ca/gp/product/052168689X/

   - Statistical and Data Analysis for Financial Engineering (Ruppert & Matteson): https://www.amazon.ca/gp/product/1493926136/

   - Reinforcement Learning (Sutton & Barto): https://www.amazon.ca/Reinforcement-Learning-Introduction-Ri...

   - Deep Learning (Godfellow, Bengio & Courville): https://www.amazon.ca/Deep-Learning-Ian-Goodfellow/dp/026203...

   - Networks (Mark Newman): https://www.amazon.ca/Networks-Mark-Newman/dp/0198805098/

   I have a ton of textbooks in my wishlist that seem noteworthy and interesting, but that I haven't gotten the chance to read yet: no promises, but you might find something in there https://www.amazon.ca/hz/wishlist/ls/1FWW046Q3RWWM

   My area of expertise is biochemistry, life science, immunology, cell bio... So if anyone wants good recommendations in these topics I have plenty! :)

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