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MIT lecture series on deep learning in January 2020

deeplearning.mit.edu

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Re: MIT lecture series on deep learning in January 2020

#11

Post by thatcat »

nothis wrote: post #9

I feel like there's about 1000 hours of high quality AI lectures available for free on the internet and while I do believe in a certain amount of selflessness in education, I am skeptical that any of that is providing more than a glimpse of what you need to know to be productive at it. In other words, there's a thousand hours of material out there, which probably takes 10000 hours to actually get into so you might as…

Studying it at a university means moving and having a certain background. While i agree that these resources are hard to break down into a curriculum, theres nothing stopping you from copying a university curriculum at home and doing work on your own...

Re: MIT lecture series on deep learning in January 2020

#13

Post by waiseristy »

So Lex Fridman curated this page and is the subject of many videos within it. Seems like Missy Cummings and Filip Piekniewski's assumption that MIT has scrubbed him from the site is unfounded.

[1] https://twitter.com/missy_cummings/status/117949700363566285...

[2] https://blog.piekniewski.info/2019/11/18/late2019-the-wizard...

Lex's blocking of dissenting opinions on twitter is still egregious though.

Re: MIT lecture series on deep learning in January 2020

#14

Post by amznthrowaway5 »

nothis wrote: post #9

I feel like there's about 1000 hours of high quality AI lectures available for free on the internet and while I do believe in a certain amount of selflessness in education, I am skeptical that any of that is providing more than a glimpse of what you need to know to be productive at it. In other words, there's a thousand hours of material out there, which probably takes 10000 hours to actually get into so you might as…

> I feel like there's about 1000 hours of high quality AI lectures available for free on the internet and while I do believe in a certain amount of selflessness in education, I am skeptical that any of that is providing more than a glimpse of what you need to know to be productive at it.

Why? Whether you go to the lectures in a university or watch them online, it makes no difference. I prefer and recommend textbooks over videos though.

> In other words, there's a thousand hours of material out there, which probably takes 10000 hours to actually get into so you might as well put all that effort into properly studying it at a university, getting the knowledge not covered in the lectures alone and a degree to prove it in the end.

What knowledge "not covered in lectures alone" or books do you need? Why do you think having a signal of pedigree somehow confers this knowledge onto people.

> If you're just "curious" about AI, a really good half hour lecture should get you up to speed.

You don't have to either be an expert or a complete layman. This gatekeeping is ridiculous. I've worked with many phds and most of them are not even close to as competent as folks who are naturally gifted and put in the work to pick up the topics.

Re: MIT lecture series on deep learning in January 2020

#15

Post by acollins1331 »

nothis wrote: post #9

I feel like there's about 1000 hours of high quality AI lectures available for free on the internet and while I do believe in a certain amount of selflessness in education, I am skeptical that any of that is providing more than a glimpse of what you need to know to be productive at it. In other words, there's a thousand hours of material out there, which probably takes 10000 hours to actually get into so you might as…

I can guarantee you there is enough instructional material online about machine learning to be useful.

source: i learned through youtube and articles and now have a career

Re: MIT lecture series on deep learning in January 2020

#16

Post by buboard »

nothis wrote: post #9

I feel like there's about 1000 hours of high quality AI lectures available for free on the internet and while I do believe in a certain amount of selflessness in education, I am skeptical that any of that is providing more than a glimpse of what you need to know to be productive at it. In other words, there's a thousand hours of material out there, which probably takes 10000 hours to actually get into so you might as…

ML is a very applied subject. There is entirely too little theory people need to know. In fact the most impressive vision/nlp architectures are indeed uninterpretable alchemy. It would make very little difference to study it at a university. Unless of course you 're going for probability theory.

Re: MIT lecture series on deep learning in January 2020

#17

Post by Vervious »

Notably, these are all winter courses, taught over the course of three weeks in January.

They don't have the formality and institutional support of a semester-long course. Often they are taught by students. MIT has a ton of people working in this area, and I'm not sure this particular group of people is representative.

Re: MIT lecture series on deep learning in January 2020

#19

Post by amelius »

nothis wrote: post #9

I feel like there's about 1000 hours of high quality AI lectures available for free on the internet and while I do believe in a certain amount of selflessness in education, I am skeptical that any of that is providing more than a glimpse of what you need to know to be productive at it. In other words, there's a thousand hours of material out there, which probably takes 10000 hours to actually get into so you might as…

For example, it would be refreshing to see a deep-learning course with math at a higher level than high-school level.

Re: MIT lecture series on deep learning in January 2020

#20

Post by codingslave »

The gap that I see in current machine learning is that everyone is learning how to use the popular models, but no one knows how to construct a new model that solves a new problem. So everyone can download word vectors and use them for what they're good at, but the second you get off the beaten track, almost all machine learning practitioners fall flat. I really dont think this is due to how new the field is, rather that very few people have the mathematical maturity and experience to actually use optimization theory and linear algebra to construct new highly specific language models. There is simply no information available about doing this. You can learn about the underpinnings of matrix factorization and how that relates to word vectors, take that further and read about eigen vectors, but still, its too thin.
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