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Comment by minimaxir | Hacker News Reader

Facebook's guide comes a couple weeks after (EDIT: FB's guide was originally published on May 7th, so it's actually a few months old) Google published their ML guides (https://news.ycombinator.com/item?id=17595611).

That's not a bad thing; the more guides from reputable sources, the better. Just don't read them and say you're an ML expert afterwards.

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>> Just don't read them and say you're an ML expert afterwards.

Too late. I get like 2 random LinkedIn invites a day from randos claiming to be simultaneously "AI" and Blockchain experts. You look at their profile and they have some codecamp course in React. I dont get it, do these people get jobs this way?

> I dont get it, do these people get jobs this way?

yes.

I wonder this too. As a relatively young professional, I regularly have folks add me who are my age or younger (mid 20's), and have a portfolio of experience that reads as if they are a Fortune 500 CEO. Combine that with having 5000+ "connections", a slew of unverified and uncorroborated skills, and LinkedIn continues to feel frivolous.

Yet most jobs listing these days require a link to your profile, so it's clear there's some value in having a "complete" profile.

There was an article on HN a few weeks ago about a guy making a game out of LinkedIn. In that he made a fake account, filled it with buzzword skills, degrees, and colleges. Started adding every notable person he could. Then it became a domino affect. Once he had some influential people as connections, other people started adding him, thinking he was then a big shot. Then once he got a ton of influential connections, recruiters from major companies started reaching out to him with job offers and interview requests.

Ultimately LinkedIn does have a good business use, but it can also be gamed pretty hard.

EDIT: Found the link. It didn't originate on HN, but I saw it from a post about it on HN.

https://theoutline.com/post/5495/how-to-beat-linked-in-the-g...

Thank you for sharing, Fun read

They don't, otherwise they wouldn't have to spam LinkedIn.

Can't the inverse also apply?

If it didn't work they wouldn't spam LinkedIn.

No, they don't really, which is why they're always out and about making noise. The good people just keep getting promotions and salary increases and don't spend a lot of their time "networking." When's the last time you got a LinkedIn spam from Jeff Dean looking for a job?

Well they do get some jobs, they just don't happen to keep them for very long...

I had to block one because they kept asking me to endorse and recommend them for shit that I don't even know about.

I'm like dude, when did you ever worked on "designing collimation towers" for NASA? You are like 19. Unless you were like a child prodigy, which I doubt, since you are asking me for an endorsement.

I don't think anyone's said it better than Joel Spolsky in his 2006 article on why bad developers are over-represented on the job market:

https://www.joelonsoftware.com/2006/09/06/finding-great-deve...

I feel like the timing is more related to this: https://news.ycombinator.com/item?id=17706997

It may be just a coincidence but I have started noticing that very often when a company has a post that criticizes it for some behavior trending another post immediately follows showing the "generosity" of the same company showcasing some OSS or a blog post about some popular technological subject.

It got me thinking that maybe those companies have bots ready to upvote nice things about them when some criticism surfaces.

I've seen this happen with both Google and Microsoft so far.

I think you will find that large companies attract criticism continually, and release open source software continually.

Well then. Your 2 cents on how to become one after going through those videos? I am genuinely asking. Looking for a career in it. At the beginning now. Read a fair bit, basics videos and all that online. Nothing formal. Can do a bit of c, c++.

I strongly recommend doing personal projects with ML, particularly projects/datasets that haven't been done before. (i.e. not that Titanic dataset or sentiment analysis of Trump's tweets)

Like anything... do it. If you have the academic background get an entry level job. If not, you'll have to build things using ML.

Of note, there aren't really any entry-level ML jobs (Data Analyst isn't the same, although would be a valid stepping stone).

Sure there are.

I get freelancers to do data preprocessing for me frequently, and sometimes put it through some off the shelf model.

Generally it's hard to find the right people for this, but that isn't exactly unique.

Work through a ton of Coursera courses and implement your own projects. If you don't know what projects you could do, you can use Kaggle to get ideas and datasets.

The MOOC courses are "just" there to teach you the basics and background. Projects are absolutely necessary for you, because without a degree you will only be able to convince prospective employers based on having a lot of practical experience.

> Just don't read them and say you're an ML expert afterwards.

"ML expert" is the new "web developer"

As someone going through a Master's in CS to get into ML, this makes me a little sad..

(though I do understand what you're getting at)

Actually, the Google guides were initially published in February (and publicly available before that from Martin Zinkevich since 2016!). But I agree, it's great to see more resources around these best practices.

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