This Math book for Programmer is written and self-published by a Software Engineer Jeremy Kun who has a PhD in Math.
It is timely for IT undergraduates to have a minimum foundation in some “Applied” (*) Modern Math :
- Linear Algebra (Matrices, Eigenvectors, Eigenvalues used in Google Search Algorithm) ,
- Algebraic Structures (eg. Group for Symmetry) ,
- Calculus (eg. Gradient Descent used in ‘DeepLearning’ )
- On top of some “Pre-requisites” in High school (A-level, International Baccalaureate) Math (eg. Bayesian Probability, Statistics, etc. ).
An IT Professional without a solid Math foundation in “Applied” Modern Math is like a car or a ship without ‘GPS’ – a BIG navigation disadvantage in the new ‘IT 4.0’ frontiers (AI, Big Data, … ).
Prologue: The Journey of Self-Publishing on Amazon “CreateSpace” by the Author:
Remark (*) : The Modern Math can be divided into 2 types :
“Applied” vs “Abstract / Pure“.
Some Abstract Maths are initially ‘Pure’ theoretical and ‘useless’ in any application (quote from Prof G. H. Hardy 《A Mathematician’s Apology》), however, they turn out to be very useful in Science, Engineering and IT many decades or centuries later. Eg.
- Group (Chemistry Crystallography, Quantum Physics) ,
- Prime number (Encryption) ,
- Ellptic curve (Blockchain ECC Cryptography) ,
- Algebraic Topology : ‘Homological Algebra‘ (Big Data Analytics),
- “The Most Abstract Nonsense” Category Theory (Latest IT Paradigm ‘Functional Programming’ eg. Haskell, Scala, Kotlin)
Ref : Three Ways to “Think Abstract“