kendoka reacted to ZacoAttaco in New programmer, language question
Python is a very in demand language because of it's versatility. It has uses it automation, data visualisation and AI to name a few.
All 3 are great choices, as far as is know SQL is the simplest of the three and is better for entry-level positions, it always advantageous to have from my understanding, but it is more database focused. I personally have spent more time learning Python. I find it really enjoyable and I'm beginning to see how, with the aid of modules, how useful and versatile it truly is. I plan to keep learning.
So as a beginner, I definitely recommend learning Python, it takes time to understand how the language thinks and processes things but you'll get the hang of it. I used this Udemy course and it was truly excellent, highly recommend. I'm well ahead of my class and learning better programming habits because of it.
I found this article useful when looking for worthwhile languages and skills:
Here's another article I found useful:
Just my two cents, relatively inexperienced compared to others on the forum so hopefully they can give you some more insight.
kendoka got a reaction from Senzelian in Win10: Administrator account, but no administrator rights?
Have you checked your permissions, even if it's the only account...?
kendoka got a reaction from Loote in Free and/or Open-source Alternatives to many Common Programs
Maybe... Universal Media Server ???
kendoka reacted to straight_stewie in [Noob Question] Setting up Eclipse C++ with MinGW?
I wasn't able to find a useful tutorial for intermediate/advanced users from any date when I tried MinGW. I gave up and stuck with MSVC (the default compiler for windows since NT 3.1).
Use Visual Studio. VS2017E is free to use, and it's generally considered easiest to use Microsoft tools when developing Windows Applications.
kendoka reacted to straight_stewie in Hardware for Neural Network Training
16GB of ram will set you off for a good start, but be sure to choose a motherboard that will allow you heft upgrade options. If you stay with it, you may very well end up working with extremely large data sets during your tenure at university, and having the ability to increase the amount of RAM you can use can keep your machine up to speed.
As far as the CPU goes, something with a few extra cores/threads would be preferable, but you still want a relatively high clock speed. There is a balancing point there if you are going to be working on both small and large data sets.
kendoka reacted to reniat in Hardware for Neural Network Training
This seems relevant and useful: http://timdettmers.com/2018/12/16/deep-learning-hardware-guide/
(it was also the 2nd google result ?)
tl;dr: with a gtx 1080 I would probably go with 16GB of standard ram (don't worry about RAM speed), and something cheaper but with a good thread count like an AMD 2600.