/sci/ - Science & Math » Thread #12484490

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Anonymous Sat 19 Dec 18:22:04 2020 No.12484490 View Reply Original Report

Quoted By: >>12485795 >>12486564

Anyone here from a pure science background getting into machine learning?
God I hate sharing courses with programmers, they don't know how to think nor how to teach fuck fuck I hate Coursera fucking people explain the fundamentals stop skipping the math fuck it words aren't a replacement for equations fuck you I hate you all so much just show me the numbers dammit

Anonymous

Anonymous Sun 20 Dec 2020 00:07:23 No.12485795 Report

Quoted By:

>>12484490
I share your dissatisfaction i guess. 69% of time i spend on putting the results of my models into text that is simultaneously factual and not overly long. Because business tards cannot tolerate mathematics.
The notation is there for a reason, if you dont use it its either wrong or too long.
>>12484490

Anonymous

Anonymous Sun 20 Dec 2020 03:00:14 No.12486209 Report

Quoted By:

Went from ChemE to doing ML/DL for pharma companies. Shit's cash. OP sounds like an asshole sperg though so I hope he doesn't make it.

Anonymous

Anonymous Sun 20 Dec 2020 04:55:06 No.12486494 Report

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*ahem*
As a computer fag that got stuck with 2 barely-english-speaking PhDs for my PhD in ML, I am bailing on year 1. This field is full of buzzwords, the citation circlejerk is off the charts, and 90% of the people involved are pajeets that do incremental research.
IF you are an actual scientist, you have no reason to waste your life in a meme field.

Anonymous

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Anonymous Sun 20 Dec 2020 05:34:15 No.12486564 Report

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>>12484490
>Anyone here from a pure science background getting into machine learning?
Yeah I'm a biofag trying to learn about ML. I haven't even gotten to close to ML and probably won't actually read about ML for a year or two. If someone in ML or CS can criticize my approach or give me advice please feel free to. But here it is:
>want to get into ML
>books inform user to download and use all sorts of statistical packages
>using all sorts of commands I don't understand eventhough I took stats
>realize they use bayesian methods which I don't know about
>read bayesian stats book for a month
>realize I don't know enough probability theory
>read probability theory book for a few days
>realize I don't know enough measure theory
>read measure theory book for a week
>realize mathematical analysis is somewhat of a prerequisite
>now starting mathematical analysis after deciding on a book (my thread is still up actually)
Anyway OP, as someone who seems to be doing the exact same thing as you, this is the path I plan on taking. Seems to me like actually understanding ML from the ground up requires the knowledge of a math major and a little graduate math knowledge.

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