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Cutting Edge Deep Learning for Coders, Part 2

course.fast.ai

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Re: Cutting Edge Deep Learning for Coders, Part 2

#41

Post by bitL »

RSchaeffer wrote: post #38
poppingtonic wrote: post #37

Earlier quoted context omitted.

One year of Python, with high school and introductory college courses. Some basic linear algebra, familiarity with logarithms etc.

I think you misread my question. I'm asking what math students will learn, not what math students should already know.

Gram matrix, some non-linear optimization. Deep Learning is simple, complexity comes from loss function, trying to adjust weights of under-represented categories, different LEGO blocks in building your network and seeing if the particular non-linear optimization works in your case or not. You can go super deep with state-of-art math research in reading about "why do we think Deep Learning works, when it shouldn't", which is mentioned by Jeremy.

Re: Cutting Edge Deep Learning for Coders, Part 2

#42

Post by bitL »

colmvp wrote: post #31
jonahx wrote: post #5

Earlier quoted context omitted.

Hey Jeremy, thanks for making these courses! I was curious if you could offer any points of comparison between the fast.ai courses and the Udacity ML nanodegree course (or any other MOOCs you have opinions about).

I didn't take the Udacity ML Nanodegree, though I did do the Deep Learning Nanodegree. I found it to be disappointing especially since they had hyped the collaboration with Siraj, which was nothing more than linking to certain YouTube videos. The project feedback was sometimes helpful. I felt like most of the time though, the feedback was "you did this wrong, read this article" instead of something more personal like…

> Udacity offered a single course for say, CNN's and GAN's, going very deep into the math and processes behind them.

I think that's what are they going to do next with their AI school. They announced separate nanodegrees for CV, NLP and RL. However, I hope they aren't going to be such massive disappointments as AI ND term 2, where they basically didn't deliver what they promised, castrated projects and one could finish each of term 2 specializations in one weekend (i.e. removing image captioning project, removing real-world NLP project, etc.). A similar story happened with Robotics term 2, where instead of a real robot they promised you received a standard discount for NVidia TX2, and reinforcement learning was butchered from robot walking to robotic arm movement. So I am doubtful they can really live up to their promises with their current staff that keeps underdelivering. The only ND they made absolutely breathtaking, worth every penny, was Self-driving Car ND (IMO the best [not only online] course I've ever taken, and I took many from top 10 universities).

Re: Cutting Edge Deep Learning for Coders, Part 2

#43

Post by imnotadoctor999 »

gcmac wrote: post #20
apohn wrote: post #18

Jeremy - First of all, I just want to say thanks to you and Rachel for the course(s). I worked through part 1 (2017 version) last year and it was fantastic. I've got part 2 on my to-do list for this year. Looking at the 2018 part 1 course, quite a lot has changed (from Keras to Pytorch?) from a code perspective in comparison to the 2017 part 1 course. If I want to start part 2, does it make sense to go-ahead with the…

Not Jeremy (obviously) but having taken both versions of the course I would definitely recommend jumping into the 2018 version. The core content is the same (image recognition, recommender systems, NLP) but the 2018 version uses more cutting edge tools and has a tighter feel (as a v2 of anything usually does).

The field is changing so quickly, but fast.ai is always ahead of the curve teaching modern techniques! Hats off to them for being able to keep up, AND share that with others.

Re: Cutting Edge Deep Learning for Coders, Part 2

#44

Post by krispin »

bitL wrote: post #39
ghufran_syed wrote: post #30

Earlier quoted context omitted.

Personally, I find the questions helpful, and for everyone who's watching on video, you can skip whatever portion you like, can't you?

The thing is you can visibly see how it interrupts Jeremy; he is in the middle of explaining something, then has the face of a surprised person, loses context for a few seconds etc. Better IMO would be if he just finished a small section in its entirety then did Q&A, instead of allowing himself being interrupted all the time. And often those questions are missing the point, which is to be expected with newbies, so th…

I also find the questions very helpful. I understand for many people who already have a good understanding, these questions might be interrupting the flow. Many a times the questions his students raised were things that I had not thought of, sometimes they even stumped Jeremy. Fortunately Jeremy in most cases gives answers which vary in length, according to whether it's a concept which he will clear later, or whether it is an important concept that needs to clarified then itself.

So I think this more effective way of learning/teaching even though there is a loss in efficiency.

Re: Cutting Edge Deep Learning for Coders, Part 2

#45

Post by stochastic_monk »

YeGoblynQueenne wrote: post #35

>> Welcome to the new 2018 edition of fast.ai's second 7 week course, Cutting Edge Deep Learning For Coders, Part 2, where you'll learn the latest developments in deep learning, how to read and implement new academic papers, and how to solve challenging end-to-end problems such as natural language translation. I would really like to know how to solve natural language translation. I think everyone would. Many people h…

Machine translation is not solved, but it's reached some surprisingly improved benchmarks for accuracy, so while it's a little presumptuous to call it solved, it's not the most egregious exaggeration I've heard about machine learning this week.

Re: Cutting Edge Deep Learning for Coders, Part 2

#46

Post by pixelHD »

YeGoblynQueenne wrote: post #35

>> Welcome to the new 2018 edition of fast.ai's second 7 week course, Cutting Edge Deep Learning For Coders, Part 2, where you'll learn the latest developments in deep learning, how to read and implement new academic papers, and how to solve challenging end-to-end problems such as natural language translation. I would really like to know how to solve natural language translation. I think everyone would. Many people h…

Well, I looked at the summary, and they're implementing a Seq2Seq model for this. It is what I think of as an archetype for machine translation and chat bot tasks.

Quite a few new network architectures in this space have been updates to this model, which uses an RNN encoder and a decoder, along with attention between them and a beam search for better results.

I wouldn't call this model a solution for natural language translation, nor would anyone else. But I think fast.ai meant that they're going to explain and go through this model, and how it's helped bring a new generation of models with good performance in this particular space.

Re: Cutting Edge Deep Learning for Coders, Part 2

#47

Post by gumballhead »

ghufran_syed wrote: post #30
bitL wrote: post #22

Earlier quoted context omitted.

I am a firm believer in candid feedback; I talked to multiple people taking fast.ai and all of them took it as disturbing the flow of lectures. I really like fast.ai, it's an excellent hands-on course, so please don't get offended.

Personally, I find the questions helpful, and for everyone who's watching on video, you can skip whatever portion you like, can't you?

Same, there have been several times I have had a question and someone thankfully asks the exact one I had. And Jeremy does a great job explaining it. It really helps to get at some of the why's behind the magic.

Re: Cutting Edge Deep Learning for Coders, Part 2

#48

Post by rashkov »

bitL wrote: post #22
jph00 wrote: post #14

Earlier quoted context omitted.

Dr Rachel Thomas, the co-founder of fast.ai, is the person who takes the highest voted questions from our 600+ in-person students and passes them on to me, as I asked her to do. At least 4 different people must have wanted the question asked before she asks it. This approach helps ensure that if I haven't explained something clearly enough that I get another chance to do so, and, more importantly, keeps me fresh and…

I am a firm believer in candid feedback; I talked to multiple people taking fast.ai and all of them took it as disturbing the flow of lectures. I really like fast.ai, it's an excellent hands-on course, so please don't get offended.

Since you appreciate candid feedback, I would like to explain why I down-voted you. Your post comes off as super rude and dismissive. You may have some valid criticism to give but, take more care in how you deliver it. It's a bad look for HN.

Re: Cutting Edge Deep Learning for Coders, Part 2

#49

Post by Dibes »

paultopia wrote: post #26
jph00 wrote: post #23

Earlier quoted context omitted.

Thanks for the feedback! One thing you may be interested in, if you haven't seen it, is that you can right-click the video and copy a link to the current time code, so you can always go back to where you were (or just pause the video in a tab and return later). Personally, I really hate the Coursera approach of lots of separate short videos - I totally get that some people like it, and that's fine, but it's not somet…

Oh, I did not know you could link to specific time slices! That's a big help, thanks!

another thing I used a ton when going through part 1 was being signed into my google account, google kept track of my progress through the video and if I exited out and came back on a different machine it would resume where I last left off, then I would back up a few minutes to build that context back up (or attempt to anyways).

Re: Cutting Edge Deep Learning for Coders, Part 2

#50

Post by gumballhead »

jph00 wrote: post #2

Jeremy from fast.ai here. I've posted a summary of the course materials for anyone who's interested : http://www.fast.ai/2018/05/07/part2-launch/ Let me know if you have any questions about the material or approach. There's also a discussion for the course here: http://forums.fast.ai/c/part2-v2

Thank you for creating these courses and putting them online! I started part 1 a few weeks ago. I couldn't agree more with your teaching style. I'm someone who started college as a computer science major and couldn't finish, because it felt like I was pounding my head on the wall trying to learn abstract math when what I really wanted to do was build stuff.

I finished my degree with economics, went to work in finance, and worked my way to being a developer by first doing advanced Excel, then Access, then database servers, then web development, then native development, and now more math heavy research and development. As the need arises, I keep going further down the stack and gaining more understanding. It's much more natural (for me) to learn that way.

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