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AI Expert Roadmap

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Re: AI Expert Roadmap

#41

Post by realtalk_sp »

orange3xchicken wrote: post #34
realtalk_sp wrote: post #26

Earlier quoted context omitted.

Using a PhD as a gateway into applied ML is so horrifically misguided I hardly know where to even begin debunking it. PhDs are one especially crappy way to prove you have the intellectual chops to engage with ML. There are far more direct, practical, and expedient alternative paths to get there. Importantly, the number of people who were perfectly capable of doing a PhD but chose not to (because, frankly, it's a very…

Yikes! This doesn't really come across as a nice comment (bent minds???). There are good concrete reasons to pursue a PhD (ignoring soft reasons like pure interest): wanting a research career is one - it's pretty difficult to get hired as a scientist without a PhD. Also, historical evidence doesn't really support your claim that R&D is orthogonal to business value. Sure, pure science is often independent from $$$ (de…

I explicitly caveated my statement with "Using a PhD as a gateway into applied ML" for a reason. The vast majority of people going into applied ML are not pioneering new methods. They're using ML as a tool to support business objectives. This is the group I'm talking about.

The phrase "bent of mind" roughly implies "the way someone thinks". Its usage is declining I suppose but there's nothing connotatively nefarious there.

Re: AI Expert Roadmap

#42

Post by cambalache »

nmrcq wrote: post #15

With all due to respect to the author of the site, mastering all the materials in the machine learning or data scientist path will make you a solid 'applied' machine learning/statistical learning practitioner, but not an expert, and definitely not a research candidate. We should be careful with how we guard our scale of semantic meaning - if somebody with an undergrad understanding of statistics (frequentist statisti…

> What do we call Francis Chollet, or LeCun, or anybody else?

Ehhh, French? I like Chollet(many people dont) but he is not in the same league of Yan LeCun at all.

It seems both the author and you have a naive view of expertise in academia.

Re: AI Expert Roadmap

#43

Post by nsriv »

orange3xchicken wrote: post #34
realtalk_sp wrote: post #26

Earlier quoted context omitted.

Using a PhD as a gateway into applied ML is so horrifically misguided I hardly know where to even begin debunking it. PhDs are one especially crappy way to prove you have the intellectual chops to engage with ML. There are far more direct, practical, and expedient alternative paths to get there. Importantly, the number of people who were perfectly capable of doing a PhD but chose not to (because, frankly, it's a very…

Yikes! This doesn't really come across as a nice comment (bent minds???). There are good concrete reasons to pursue a PhD (ignoring soft reasons like pure interest): wanting a research career is one - it's pretty difficult to get hired as a scientist without a PhD. Also, historical evidence doesn't really support your claim that R&D is orthogonal to business value. Sure, pure science is often independent from $$$ (de…

Bent of mind is a phrase that means proclivity or predisposition, and PhDs are famously arduous.

Re: AI Expert Roadmap

#44

Post by orange3xchicken »

realtalk_sp wrote: post #41
orange3xchicken wrote: post #34

Earlier quoted context omitted.

Yikes! This doesn't really come across as a nice comment (bent minds???). There are good concrete reasons to pursue a PhD (ignoring soft reasons like pure interest): wanting a research career is one - it's pretty difficult to get hired as a scientist without a PhD. Also, historical evidence doesn't really support your claim that R&D is orthogonal to business value. Sure, pure science is often independent from $$$ (de…

I explicitly caveated my statement with "Using a PhD as a gateway into applied ML" for a reason. The vast majority of people going into applied ML are not pioneering new methods. They're using ML as a tool to support business objectives. This is the group I'm talking about. The phrase "bent of mind" roughly implies "the way someone thinks". Its usage is declining I suppose but there's nothing connotatively nefarious…

Yeah - I looked it up. Thanks!

Re: AI Expert Roadmap

#45

Post by tnbalsam »

amaigmbh wrote: post #32
tnbalsam wrote: post #4

Perhaps I may be mistaken, but this seems to be a very long road for a more shallow understanding of deep learning. I'd venture this was written by someone who has a more traditional machine learning background that wants new people to the industry to have that same foundation; however, I'd venture that that is a rather inefficient way to get to deep learning proficiency. If I were to give a recommendation, it would…

As for our opinion (which is just that, an opinion) why we think that the statistical foundations and knowledge about more traditional algorithms is important, it's based on the business needs and our experience. While it might seem less necessary if the goal is to "learn deep learning", it is highly relevant if your task is to "solve this business problem". Our perspective is the industrial one. And while there are…

Yes, this makes sense. I'd suggest retitling the article to be something along the lines of "ML Expert Roadmap", and then continue to flesh out all avenues. As it stands, the roadmap has really nothing to do with AI at all, but your point about not just jumping to the shiny hammer certainly rings true and makes sense. I certainly think that's the right approach algorithmically, especially if you're looking to be a more generalist data shop.

In a world of senseless marketing hype, I think it's a good idea to take the high road on this one. Reputation alone, even if less-buzzy words like ML are used in favor of AI, really carries a long ways. Plus, we're nearing the disenfranchisement hump, and AI's going to start taking a negative connotation with many businesses, I believe. Just shoot straight and I firmly believe it'll carry you for a long ways, there.

Re: AI Expert Roadmap

#46

Post by ta1234567890 »

baron_harkonnen wrote: post #21

I would not advise anyone to go down the "data science" career path at this point, unless one of these topics is a true passion of yours and you can't imagine doing anything else (and even then I would recommend alternatives if possible). The explosion of AI/ML/Data Science teams in places that they really don't belong is going to have major backlash soon. The market is currently flooded with desperate PhDs who have…

> The explosion of AI/ML/Data Science teams in places that they really don't belong is going to have major backlash soon

I'm not disagreeing with you, just curious, did that happen with Big Data teams? If not, what happened with all the people working around that concept a few years ago? Might be an indicator of what could happen to DS teams.

Re: AI Expert Roadmap

#47

Post by NhanH »

ta1234567890 wrote: post #46
baron_harkonnen wrote: post #21

I would not advise anyone to go down the "data science" career path at this point, unless one of these topics is a true passion of yours and you can't imagine doing anything else (and even then I would recommend alternatives if possible). The explosion of AI/ML/Data Science teams in places that they really don't belong is going to have major backlash soon. The market is currently flooded with desperate PhDs who have…

> The explosion of AI/ML/Data Science teams in places that they really don't belong is going to have major backlash soon I'm not disagreeing with you, just curious, did that happen with Big Data teams? If not, what happened with all the people working around that concept a few years ago? Might be an indicator of what could happen to DS teams.

I have heard hiring managers explicitly saying that data engineer role on your resume is considered a negative point for them.

Re: AI Expert Roadmap

#49

Post by karussell »

I assumed a tech article and first read "AI extracts roadmap" like https://mapwith.ai or https://github.com/Microsoft/Open-Maps ;)

Are people really planning their carrier like this? Isn't it more that you either work for some company nearby, or a company you know by some luck or explore the AI/ML topics you or your professor likes and you got stuck? (or you start disliking it and try hard to find something else)?

Re: AI Expert Roadmap

#50

Post by morelandjs »

baron_harkonnen wrote: post #21

I would not advise anyone to go down the "data science" career path at this point, unless one of these topics is a true passion of yours and you can't imagine doing anything else (and even then I would recommend alternatives if possible). The explosion of AI/ML/Data Science teams in places that they really don't belong is going to have major backlash soon. The market is currently flooded with desperate PhDs who have…

There’s a lot of truth in this, but I find the people that pivot toward practical software engineering skills early in their PhD are still highly valuable to tech companies.

I think the issue here is you can’t become highly skilled in software engineering overnight, and compensating by flexing softer “problem solving skills” isn’t enough to compensate. If you want to be effective in data science, you need to commit to being a rockstar programmer AND statistician AND be well versed in a number of different algorithms.

Unsurprisingly, this is difficult, and so the market of people who do it well is small. That’s not, however, a referendum on the value of predictive modeling and software engineering. I don’t see advanced math and software engineering skills going out of fashion anytime soon, simply because they are hard to acquire and immensely powerful in the right hands.

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