Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Ask HN: In 2022, what is the proper way to get into machine/deep learning?

news.ycombinator.com

Post reply on HN
Print view View original

101–110 of 211 posts

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#101

Post by psi75 »

bsenftner wrote: post #90
badpun wrote: post #80

Earlier quoted context omitted.

> I’ve kinda developed the view that large organisations come to mirror the Russian Communist Party. Only the ones which have an unkillable cash cow. So, I suspect Google or large banks are mostly like that, but places like SpaceX or even large consulting firms (Delloitte, IBM etc., where managers essentially eat what they kill) cannot allow themselves to degenerate into a Chinese court.

Now this is interesting. I've always found it fascinating that when profit is on the table, democracy is nowhere to be found. I've looked, not too hard TBH, for essays and literature discussing the correlations to business model management structures and government/nation political hierarchies - not education level (propaganda), but critical analysis. I've been an employee of several of the top corporations on our pl…

Unfortunately, the only way to prevent hierarchy is to create a limited hierarchy (this is the purpose of constitutions) a priori; hierarchically naive organizations fail on this account. External parties will demand hierarchy simply because they want to know your organization (or nation) isn't wasting their time--no one wants to deliver a sales pitch to people who can't authorize purchases. If they're not careful, a group of people can end up in a state where the necessary-for-external-relations hierarchy becomes a total one. You see this with startup founders; the one who talks to the investors the most ends up in charge, and the ones who deal with employees or low-status counterparties lose power. This is why "flat" organizations can't really work; people who need things from the organization demand to know who to talk to in order to actually get things done, and eventually those "who to talk to" people end up with informal, then formal, power and it's very difficult to get them to give it back.

The large-scale failure of democracy that's happening all over the world is something different, though. Regulation is struggling to keep up with technology, and it doesn't help that nation-states have already been doing a piss-poor job of protecting people from their employers. If the US falls in the next 20 years, it won't be due to Covid or Trump or nation-level adversaries; it'll be due to the obscene power given to employers, who can literally ruin an employee's life--not just fire him, but anally ravage him in perpetuity with bad references--for any reason or none. Eventually, unless national governments start dropping serious lead pipe on employers' heads, people are going to tire of paying 30+ percent of their incomes to a government that lets bosses get away with this shit.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#102

Post by liquorice »

alanfranz wrote: post #47

My 2c (not exhaustive for what you want to do, probably): 1) Get some statistics/probability basics. It's full of people (you can see a lot of analyses on Kaggle) that "do machine learning" but make very silly mistakes (e.g. turn categorical data into a float and use it as a continuous variable when training a model). 2) take a look at traditional machine learning approaches. Nowadays you're swamped by DL (a lot of g…

They are probably not silly mistakes. Label encoding can be very useful for tree based models when the categories are ordinal, or when there are a high amount of categories.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#104

Post by depr »

psi75 wrote: post #71
bitL wrote: post #36

Earlier quoted context omitted.

Data Engineer is the outsourced part of what no ML researcher wants to do - a thankless, high-pressure, dead-end job which in no way leads to actually doing ML later - it would pigeon-hole the OP as unfit for real ML. The best way is to take Stanford Deep Learning courses at SCPD, build a reputation, do real ML work (even if it's not a PhD, it's the same courses Stanford PhDs take).

I agree with your first sentence. I'm not sure I would recommend SCPD. If you want to do real ML work, you pretty much need the PhD. This is a hard thing for people who have 140+ IQs but do poorly for whatever reason with formal education to accept, but it's true. Even if you get one real ML job without a doctoral degree, you won't get a second one. Sure, other 140+ IQs can recognize very smart people with only (or n…

I don't think what you consider "real ML work" is what OP is asking for. While they wrote "research", the three points they wrote at the end is not research, and I don't think they want to be an academic and/or write any papers.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#105

Post by zivkovicp »

psi75 wrote: post #71
bitL wrote: post #36

Earlier quoted context omitted.

Data Engineer is the outsourced part of what no ML researcher wants to do - a thankless, high-pressure, dead-end job which in no way leads to actually doing ML later - it would pigeon-hole the OP as unfit for real ML. The best way is to take Stanford Deep Learning courses at SCPD, build a reputation, do real ML work (even if it's not a PhD, it's the same courses Stanford PhDs take).

I agree with your first sentence. I'm not sure I would recommend SCPD. If you want to do real ML work, you pretty much need the PhD. This is a hard thing for people who have 140+ IQs but do poorly for whatever reason with formal education to accept, but it's true. Even if you get one real ML job without a doctoral degree, you won't get a second one. Sure, other 140+ IQs can recognize very smart people with only (or n…

There is a lot of truth in this comment; it's not pleasant, but it's truth nonetheless.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#108

Post by dmc-au »

1. Watch the 3blue1brown neural network series for a gentle refresher on the underlying maths and the big picture of neural networks (and to be inspired): https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_6700...

2. Run through the catalogue of StatQuest videos for topics of interest in machine learning etc. This includes step-by-step maths and code explainers: https://www.youtube.com/c/joshstarmer/playlists

3. Watch more 3blue1brown videos if you need to step further back to refresh on calculus and linear algebra (that's most of the maths you'll need).

If you're hooked and can't get enough of the above content, then congratulations and welcome to the Matrix.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#110

Post by jokoon »

I recently asked reddit how to label images by downloading a pre trained network that used image net, I got no answers.

I don't know how long it would take to train such network with a cheap laptop.

There are tutorials, but I don't see any cookie cutter thing.

I thought there would be demos for this, since image labeling is an old problem.

Post reply on HN