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Search - "maths is everywhere"
'Epiphany' might be overstating it, and it's something I realised a long time ago, but it's been invaluable in the years since.
When designing an interface or an abstraction or a data structure, everything is going to be easier in the long run if you can map it to a mathematically simple idea. Documentation, validation, bug fixing, interaction with other components — everything.
Contrapositively, if a piece of code is a horrible bug magnet, or hard to describe, or full of special cases — these things tend to go together — then chances are it doesn't model a logically simple concept.
Even mathematicalizing something like recursion as the limit of something like 'let g = f in f g' — making explicit something that is implicitly complicated — can provide both a cleaner API and more control over the process of execution.4
(disclaimer: this might sound like a 13 year old guy just coming out from a theater after watching matrix but in some ways, its not )
Why the fuck should i feel discouraged from getting into ml/ai by all these smart ass people continuously taunting that "yeah, you might get into ml/ai but you won't get successful if you have a bad maths"
Ok, 1) i totally agree with these guys. Checked some pages and everywhere itse regression ,linear something, nlp's and neural networks, which even by the name sounds full of maths. BUT here is a thing:
1) All i can think of this as an ocean: just like web development is so vast, android is so vast, i can assume this to be so vast too.
BUT I WANT TO APPLY IT, NOT MAKE IT! why? Because that's what a beginner would do. It's data "sciences" and ppl who are deep into it will be called data "scientist" , a fuckin doctorate profession!
And toda i see it at so manypaces : from alexa playing song to google searches , youtube recommendation, hell even coffe machines are getting smarter!
I like these things and want to apply them as a developer to my apps and websites. But tell me, do everyone making a scanner or search engines learns regression algorithms and lambda calculas?
I love automation. So much that if given a chance, i would make robot to fuckin suck me off! From smart searches , self driving cars, map routes to latest apps with awesome pattern recognitions, i love them all. What i want to do is to look at some codes, tweak them for my usage and make something extraordinary and automated machine learning from ussr's interaction. I don't think my interest to learn applications of a technology and not the technology itself should be considered wrong because both are a carreer in their own! Learning ml/ai vs learning their applications is like a learning physics vs learning furniture designing: one being a part of other but completely existential on its own .
Thus the question comes what should i do? I got attracted by ML's achievements and fireworks but every ml course wants me to be the cracker maker! I want to get into data sciences bcz of its achievements ; and i want to replicate them again nd again until get termed as a professional nd if i feel the urge, maybe re visit my collage books and read maths and get into nlp designing (or whatever)
Where to get knowledge of this "life automation technologies" / data sciences (if they both are rea equal) and knowledge of such "ml toolkits" , if its really possible to be into ml without maths?8