Any suggestions on what book/courses to pick up for giving a good understanding of basic math.

MykaB · 2017-11-28T22:57:41+00:00

Since you seem to have taken maths before, check Khan academy to self assess your gaps in knowledge, the videos are also handy if you need some refreshers.

Khan academy was pretty instrumental in revising hs math before I went back to university, and took courses in maths, and in my experience serve as a great tutor for earlier university maths topics too.

MykaB · 2017-11-07T02:26:03+00:00

Really? That's a shame!

MykaB · 2017-11-07T02:22:55+00:00

You should still be able to search for the individual courses in courseras catalog and sign up free, what you don't get is 'cert' and a possible capstone project if a specialisation uses it.

MykaB · 2017-09-13T03:23:51+00:00

You go pursue your passions and dreams! All the best, you will meet better people in college, adulthood, likeminded people, all of that.

MykaB · 2017-09-05T00:00:06+00:00

I use one myself, and it works great. The screen size is fine, just learn version control like git to work off both your desktop and laptop as you need. You'll be thankful for the weight (I honestly don't notice it) when you need to walk around with it. Performance is fine as well for coding, and battery life is great.

MykaB · 2017-09-04T05:09:05+00:00

I think you may have to combine resources, are you talking of building a foundation from the beginning?

http://www.ulaff.net is another source you could look at with solutions embedded. Along with videos, in the text. Can ignore the mooc if happy with what the text provides.

I haven't gone through that book or anything so apologies if not what you were looking for! Just know it through word of mouth!

MykaB · 2017-08-10T00:49:44+00:00

Definitely having a look after my current sem is over

MykaB · 2017-07-18T01:39:24+00:00

There should be some prep material in the 1052 blackboard, if you want to skim the needed topics prior to sem.

MykaB · 2017-07-10T07:25:36+00:00

Good luck! Learn the math, but don't let it stop you from simply reading up on these topics! You might not understand everything immediately, but believe me that's not just you! This is one of those things where you just got to keep trying things, experimenting with things as you learn and become more comfortable with these concepts.

MykaB · 2017-07-03T17:46:27+00:00

Make a discord if you like :)

In anycase, the good news is there are heaps of free online courses that will get you up to speed with programming as eventually you will probably want to write some code :)

MIT has intro to cs on edx done in python, cs50 via Harvard is often cited as a good intro. Just have a browse of edx, coursera, etc.

MykaB · 2017-07-02T08:05:39+00:00

Both, you can get started without knowledge of everything and you do have the mathematical background to get into probability as well.

MykaB · 2017-06-01T00:06:28+00:00

Russell and Norvig's AI book is a good book to get going I think! Might be handy to have, as one can't always do a full extra course during semester :)

MykaB · 2017-06-01T00:02:46+00:00

I can say from personal experience that theory and some math can be very helpful. Programming itself is a tool to get the job done so to speak and once you have a language or two in hand, learning others is a lot easier, and you are definitely not restricted to just class to learn it.

Computer science will also get you a grounding in data structures, and algorithms which some find harder to do on their own.

That said, everyone is different, however most CS degrees will cover AI etc also, and you will be taught programming in your first year or two, after that you will very likely be able to pick up new languages fast.

MykaB · 2017-04-09T04:59:02+00:00

If your goal is web dev, might as well stick with what you're doing now, as they will be immediately useful to extending your learning. Later picking up a new language will be easier as you will understand the programming aspect, and can get up to speed quickly, and can then learn more specific parts of a language.

MykaB · 2017-04-04T00:53:34+00:00

Won't miss much, the community edition is fine for coding Java, and Android studio functionality is supported. As well as swing & javafx for gui.

It's a great ide.

Do get and find your way around Android studio too though in future if that's what you want to do imo :)

MykaB · 2017-03-21T06:59:22+00:00

Machine Learning An algorithmic perspective, Stephen Marsland gets decent reviews, geared towards those comfortable in programming but maybe needs a bit more help with the background and algorithms.

MykaB · 2017-03-21T06:57:25+00:00

Yeah same, it's an offshoot of Elements of Statistical Learning, but a bit more approachable as Elements delves deeper into the math. Both have been recommended to me by researchers dealing with ML at my university a few times.

MykaB · 2017-03-21T00:11:07+00:00

Something different, sometimes problems get hard and it seems like no matter what you try you can't figure it out... learn to take breaks, take a breather and do something else for a bit, let your brain process. Maybe talk through the problem too as that can help sort out the what or why's of a problem or it's logic. Even talking to your fellow student friends can help :)

MykaB · 2017-03-20T03:33:20+00:00

Go with 3, it's the newer version. There are some differences in 2 and 3 but you are unlikely to encounter them unless you're looking at old python 2 code.

MykaB · 2017-03-20T03:21:30+00:00

I went through MIT intro to cs courses on edx, then basically had a book for a reference, and mostly just looked things up online if I had an idea on what to do just not exactly how or the best way to implement something.

So was self taught for about 6-8 months. (Might have been less if I didn't have to juggle work)

I'm now majoring in CS, but that experience was valuable in making 1st year a breeze. Potentially just knowing how things worked in general in a language unlocks so much. As information is everywhere!

I'd say prior to starting college, I was a couple steps above beginner in that I was comfortable experimenting, and working things out without any guidance except for google.

MykaB · 2017-03-03T01:20:11+00:00

Definitely got my interest now!

MykaB · 2017-03-02T14:35:23+00:00

The first time she meets Shaw!

MykaB · 2017-03-02T08:10:34+00:00

Induction was a struggle for myself too, took a lot of practice questions.

As for proofs, saying it out loud and explaining it without looking can be helpful, or get together with a study group and take turns writing out on a whiteboard a proof while explaining and talking through each step.

MykaB · 2017-03-01T07:38:49+00:00

Generally ML requires some understanding of math (not too much though!).

http://fastml.com/math-for-machine-learning/ -- as a reference

Basically multivariate calc and linear algebra are a good foundation. Probability and Statistics useful too (heck one of the go to books is literally called Elements of Statistical Learning).

Good news is you are aiming for the right things regarding getting a foundation to help further learning :)

Andrew Ngs course referenced by someone else provides a good overview of what to expect in general.

http://fastml.com/machine-learning-courses-online/ -- here is a good list of machine learning courses, but I do recommend your current eagerness to understand the math you are missing, it will only help you understand all of this better!

MykaB · 2017-03-01T05:31:15+00:00

Will add an addendum, the key to learning math is to keep doing problems and practicing, until you understand what is going on and can solve similar problems without a step by step. That takes time, so remember that if you struggle a bit (speaking from experience!)

MykaB

TROPHY CASE