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I've been eyeing this book to help bridge some gaps in the same area for me: https://amzn.to/2OZUIlE It talks more fully about mathematical proofs in general, but it gives a really good introduction to the notation and such in a much more compact space than most other ones I've seen.
Kagerjay · 2018-05-16 · Original thread
Math is something that needs to be learned by rigorous practice

I find it helpful to first learn the theory via 3blue1brown

https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw

I'm currently working through the bookofproof math problems found here

https://www.amazon.com/Book-Proof-Richard-Hammack/dp/0989472...

It goes into how to actually write mathmatical proofs / discrete math which I believe is extremely important to any math branches and computer-science in general.

I was lucky to have a great foundational math background in highschool, my calc 1/2 teacher was considered one of the best in my state. I practiced at least 30 problems every night in that class for 2 years

dmix · 2017-06-18 · Original thread
A good entry point are one of these books which start from the very beginning of math in Egypt/Greece and teach the fundamentals of math through a narrative as humans discovered the various parts:

"Mathematics for the Nonmathematician" https://www.amazon.com/Mathematics-Nonmathematician-Morris-K...

or

"Mathematics for the Million" https://www.amazon.com/Mathematics-Million-Master-Magic-Numb...

Of the two I prefered Kline's book but they are both good, albeit a bit heavy on geometery as that was a big focus of early math research.

Another great starting point is "Book of Proofs" and "Introduction to Mathematical Reasoning" to give you a deeper sense of how to approach the subject.

https://www.amazon.com/Book-Proof-Richard-Hammack/dp/0989472...

https://www.amazon.com/Introduction-Mathematical-Reasoning-N...

From there I went down this path (the order of which is up to you, each has tons of good source material):

-> Proofs/Logic

-> Algebra

-> Linear Algebra

-> Calculus

-> Abstract Algebra

-> Set Theory

-> Group Theory

-> Category Theory

-> Statistics/Probability

-> Discrete Mathematics

I never did well with learning math in a classroom but I've grown to love math through this process. There are lots of applications in programming as well. It makes approaching the deeper parts of Haskell/FP, data science, and machine learning much more accessible. I particularly liked the higher level Abstract Algebra stuff over the more grinding equations of calculus/linear algebra as it was more similar to programming.

dmix · 2017-04-21 · Original thread
Reminds me of the MIT SICP lecture videos from the 80s. The concepts of black box abstraction and the simplicity of using LISP like lego building blocks blew my mind and made me switch from being a UX designer dabbling in Rails to a full blown programmer.

It was still entirely relevant to today even though it was a few decades old as the fundamentals of computer science are still fundamental.

https://www.youtube.com/watch?v=2Op3QLzMgSY&list=PL8FE88AA54...

Hearing that intro music still brings a smile to my face.

I just happen to be relearning math right now as I dive deeper into data science and this is perfect timing. Going to watch this series once I get through my math proofs book ("Book of Proof" by Richard Hammack which I recommend to people getting into math https://www.amazon.com/Book-Proof-Richard-Hammack/dp/0989472...).

jordigh · 2015-08-26 · Original thread
This stuff is usually rolled into courses called "abstract algebra". If a textbook is called "abstract algebra", it's usually designed for a first year undergraduate. If it's just called "algebra", it's usually aimed at a more mature audience. Herstein and Hungerford are the texts I learned from. This book seems more recent and popular:

http://www.amazon.com/Book-Proof-Richard-Hammack/dp/09894721...

The other big stream of basic undergraduate mathematics is analysis. For that I recommend Spivak's Calculus.

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