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Sort of. That would absolutely be "allowed". Now whether that is useful to write out, depends on what problem you are trying to solve.

Here is another example

> Does the book cover all the relevant parts

No, it isn't quite so comprehensive, but it will absolutely help you get started and help you decide if you want to learn more.

agentultra · 2018-05-15 · Original thread
Read some books, practice exercises, and find an area of interest.

Start with some liberal-arts introduction to a particular topic of interest and delve in.

I often find myself recommending Introduction to Graph Theory [0]. It is primarily aimed at liberal arts people who are math curious but may have been damaged or put off by the typical pedagogy of western mathematics. It will start you off by introducing some basic material and have you writing proofs in a simplistic style early on. I find the idea of convincing yourself it works is a better approach to teaching than to simply memorize formulas.

Another thing to ask yourself is, what will I gain from this? Mathematics requires a sustained focus and long-term practice. Part of it is rote memorization. It helps to maintain your motivation if you have a reason, a driving reason, to continue this practice. Even if it's simply a love of mathematics itself.

For me it was graphics at first... and today it's formal proofs and type theory.

Mathematics is beautiful. I'm glad we have it.


Update: I also recommend keeping a journal of your progress. It will be helpful to revisit later when you begin to forget older topics and will help you to create a system for keeping your knowledge fresh as you progress to more advanced topics.

agentultra · 2018-02-22 · Original thread
Graph theory is amazing. One of my favorite subjects.

If you're a liberal-arts kind of person and or have scars from prior experiences with mathematics I recommend,

agentultra · 2017-11-20 · Original thread
A more graduate-level book but one I found pleasing:

A Logical Approach to Discrete Mathematics:

And a more pragmatic approach to the same material (with a lot of cross-over in terms of proof-style, etc):

Programming in the 1990s:

But one I particularly enjoyed early on was written for liberal-arts level students of maths (who might've been traumatized by maths in the past):

Introduction to Graph Theory:

It will actually get you into writing proofs in set theory within the first couple of chapters.

anaphor · 2013-12-28 · Original thread
Here is a great one:

"A stimulating excursion into pure mathematics aimed at "the mathematically traumatized," but great fun for mathematical hobbyists and serious mathematicians as well. Requiring only high school algebra as mathematical background, the book leads the reader from simple graphs through planar graphs, Euler's formula, Platonic graphs, coloring, the genus of a graph, Euler walks, Hamilton walks, and a discussion of The Seven Bridges of Konigsberg."

mindcrime · 2012-08-13 · Original thread
There's also stuff under "Network theory"[1] at Wikipedia. I feel like those two articles should probably be merged, but it hasn't happened yet, and I haven't had time to take a stab at it. But anyway, both articles contain some useful info.

I also recommend these few books as a good starting point:

Network Science: Theory and Applications[2]

Linked: How Everything Is Connected to Everything Else and What It Means[3]

Six Degrees: The Science of a Connected Age[4]

The Wisdom of Crowds[5]

Nexus: Small Worlds and the Groundbreaking Science of Networks[6]

Diffusion of Innovations[7]

Of course - being that Network Science is a multidisciplinary field, that touches a lot of other areas - it can be hard to get a handle on what to study. But those few books - between them - cover a lot of the basics and would give somebody who's interested in this stuff enough background to figure out where to start digging deeper.

For a little bit more on the technical side, a couple of good resources at:

Introductory Graph Theory[8]

Introduction to Graph Theory[9]

Algorithms in Java: Part 5 - Graph Algorithms[10]











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