Whats a better career ML or NetSec

im a stoner and i cant work around people. But im very interessted in Machine Learning but im to lazy for math. I also like network security so which 1 is a better fit for a lazy but curious stoner?

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ML. Security involves talking to people a lot more. Honestly, once you understand how it works it's easier as well, at least from the perspective that you're not constantly trying to keep up as much. ML obviously has stuff to keep track of, but it moves more slowly. Hard part of ML is just getting the math, learning all the different tools, knowing which models to use when etc.

while I don't know too much about netsec, I'm pretty confident that it's more difficult than ml. I think that getting a data science job or whatever is way easier than getting a netsec job.

ML is easy enough for a stoner

>I do ML, roomie is Jow Forums hakker god

and which is better to make money off of it right away
do i even stand in ML a chance to monetize my knowledge right away.

I could afford to just learn ML for 1 or 2 years without worring about money to much- but i like money and wth netsec its easier to make a buck on the side- how is it with ML are there some good money making things - i want to know how much knowledge is needed to make money

>too lazy for math
>wants career in ML
Yikes

isnt math nothing but copy and paste aswell, i think pretty much every formular is to find online and im sure there are tutorials on how to apply that correctly aswell so how hard can math be?

> lazy ass stoner picking between two fields that require intelligence and discipline

so should i say fuck it and go to the millitary?
there is neither 1 needed

if you cant do math forget about ML lol.

You can be in netsec and not smart, but you have to be disciplined. You cant be neither.

Also, army will require hard work and discipline, so how bouts you just get off your ass

the math isn't hard. if you can do netsec then you can do the math ml requires. there is pretty much no advanced math needed. well, except for theoretical work in academia. everything you would need at a job is linear algebra and analysis.

thatswhat im trying to do, im tired of making UIs and basic backend work
Im fascinated by AI and ML and Data science and this shit primarily because this will be the future and i want to get my foot in the door.
I just want to figure out whats the easiest way to make the most money

netsec is not easy at all btw.

even for the fundamentals you need to understand and be eloquent with network protocols and network topology, and then there's virtual networks on top of that. and it's just the fundamentals and there's a very long way up from that.

i have a basic understanding of CS and coding and network stuff- im just trying to find a goodway to dig deep and make a killing doing so

Netsec evolves super fast because you have to wake up at 4am to patch the 0day that just came out before some Jow Forums edgelord breaks into your server and steals your BTC and customer CCs. It's not at all easy but it pays well if you're good at it

>fascinated by mother fucking regression

i know it requires constant learning threfore i tend more into ML simply because i think its easier to train a computer plus you already have all the frameworks and librarys that you can apply which you dont have in liek netsec with 0 day exploits and constant new waays of scamming people comes out all the time

Get balls deep in kubernetes, and continuous security. That will make you the money.
If you can get into kafka, apache spark, arrow, that all leads to big data and ml too

Google cloud has some awesome ml shit you can throw data at to play with it

And look at dremio

Fascinated by Quantum Mechanics / Molecular Biology etc. Never got fascinated by current trend of DeepLearning-AI. Interesting read would be “Algebric Mind” for a different perspective.

>Quantum Mechanics
Quantum chips on silicon soon (tm) bro

Entry barrier for NetSec is still high, but with lots of tooling a DataScientist usually focuses on model selection and feature engineering. Unless you are a ML Researcher, product managers will call all the shots in typical enterprises / companies. Only place stat/math is useful is finance / Insurance. Unfortunately ML is really tricky to apply to Time series data. Good luck.