/sci/ - Science & Math

Our course covers several sections out of our math text per course. We speed through the sections and their definitions/theorems/proofs. There is absolutely no way anyone in course follows every rigorous deduction/proof at this pace.

I have been reading the relevant text ahead for each lecture, but it takes up 4+ hours of my time to read 2-3 sections for us to only speed through it in an 1 hr 30 minutes of lecture. We cover between 4-5 sections per week out of the chapter so this is about 8-9 hours of reading/doing proofs. It feels almost unsustainable as my other courses are neglected.

I am pretty certain I understand the math course better than majority of the people in my class, as I can tell whenever we are doing complicated proofs (ones I've ruminated hours over) in 2 minutes in class people just nod their heads and I know full well they haven't had time to process the tricks and subtleties of the proof.

Should I feel bad if I don't finish the 2-3 sections prior to class? I am covering 90-95% of the reading before each class and then finish the remainder when I have the time.

I don't like to speed read through the proofs. I like total understanding. Most of my classmates told me they don't even read the book lol.

>>8615645
I'm doing this now. I did pure math undergrad and switching into CS. I have to take a lot of undergrad CS courses. Last semester was in a freshman programming course and was a top student despite being out of school for 4 years and not knowing how to code well. Already doing very well in second programming course & also sitting in a discrete math course (my pure math degree didn't have math courses that were very applied to CS topics) and am on top of it too. Kek I'm "that guy too". Luckily I still pass as 18-19 so I don't look out of place.

I am looking for online sources that teach Machine Learning.

Looking for something that teaches you the math + allows you to do programming projects.

I've seen some like:

https://www.datacamp.com/

But not sure if they are worth going through.

Any recommendations?

>>8197620

OP look at,

http://www.math.harvard.edu/~knill/teaching/math21a/nash.pdf

https://answers.yahoo.com/question/index?qid=20080501140727AAb2Ys1

>>8123102
Similar

>Little kid in elementary school
>Library day
>Required to do a reading program where they test you on your reading recall ability
>All the books in this system are fiction based
>Hate fiction
>Go to science reading section
>See book on physics
>Read through the book the entire year
>Decide I will major in physics
>Read several physics books throughout the years
>Take intro to physics in college
>Get an A
>Take a more serious course in physics
>Terrible 1st year professor
>He was horrible at explaining anything
>Physics professor quit the university after that year
>Decided I hated his course
>Didn't take another physics course
>Found I liked the math behind physics more than physics
>Became a pure math major
>Graduated with pure math degree

>>8011711
Discrete Math
Data Structures
Algorithms

I would supplement those courses with Calculus I-III, Linear Algebra, Abstract Algebra, Analysis, Mathematical Logic (Advanced course)

Are the three "most important" CS courses you need to take. Ignoring OS, and other "applied" courses.

You can go into many different areas:

Artificial Intelligence; Computation and Language; Computational Complexity; Computational Engineering, Finance, and Science; Computational Geometry; Computer Science and Game Theory; Computer Vision and Pattern Recognition; Computers and Society; Cryptography and Security; Data Structures and Algorithms; Databases; Digital Libraries; Discrete Mathematics; Distributed, Parallel, and Cluster Computing; Emerging Technologies; Formal Languages and Automata Theory; General Literature; Graphics; Hardware Architecture; Human-Computer Interaction; Information Retrieval; Information Theory; Learning; Logic in Computer Science; Mathematical Software; Multiagent Systems; Multimedia; Networking and Internet Architecture; Neural and Evolutionary Computing; Numerical Analysis; Operating Systems; Other Computer Science; Performance; Programming Languages; Robotics; Social and Information Networks; Software Engineering; Sound; Symbolic Computation; Systems and Control

http://arxiv.org/

>>7992129
Leave the Physicist alone.

As a fellow with a BS in pure mathematics I have a love/hate relationship with the field. In some ways I cannot see myself frittering away over useless puzzles.

So, I tried to be applied and really hate the hype around data science/big data as most of what I've seen were people using programs (R, SAS, etc) to utilize statistical libraries they don't understand the inner-workings of and then have the guts to call themselves 'data scientist' while claiming to be able to interpret the results. These are the very people who are good with 'business speak' and say things around business oriented processes to sound intelligent, why? Because they understand the interoperability of how a businesses function, can use a few meme words and can use what little they know to create BS that sounds good, but is actually lacking in substance. Do I want to be a associated with that? No.

Then I ventured in to computer science and most people I come across associate computer science to programming. I am strong in the math but was weak in the programming so started to learn a few programming languages to supplement the mathematics. As a noob learning programming I came across strong programmers that are weak in math and then all they want to talk about in CS is software engineering but never the data structures or algorithms or program complexity. So now I'm learning programming (more as a means not an end) and I'm surrounded by a group of people that SEE programming as an ends and never beyond it. Do I want to be a software engineer? NO.

So lately I've been gravitating more and more towards theoretical mathematics because I find it more interesting/enlightening than the above.

I decided I'll probably get a PhD in CS, do some theoretical things, but learn some applied so I am not forced to be in academia.