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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

#31

Post by colmvp »

jonahx wrote: post #5
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

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 an elaborate explanation on why you should do things a certain way. I even once explained why I initialized a model a certain way and the reviewer ignored it when critiquing my model, which almost felt like "all students have to do it this way."

It wasn't all bad. My favorite parts were learning about GAN's with videos and a notebook from Goodfellow. And when I was trying to build more intuition about CNN's, the videos with Vincent Vanhoucke were helpful.

But altogether I felt a little disappointed in the actual projects. Maybe it was because I felt like the math was glossed over and it was too many topics with shallow exploration for a single course. I actually wished that Udacity offered a single course for say, CNN's and GAN's, going very deep into the math and processes behind them.

I'm taking another Udacity course taught by Thrun (this time, it's free) and again, he kind of glosses over why certain mathematical operations are done, at which point I spent a lot of time watching lectures by other professors who spent more time explaining it.

I think that's my biggest criticism about MOOC's in general, they can be very hand-wavy about very important concepts that underly a process. I've spent a great deal of time reading papers and course material from other colleges, writing throw away code, and watching videos from other profs in order to shore up an intuition that was simply not strongly built by the MOOC.

Re: Cutting Edge Deep Learning for Coders, Part 2

#32

Post by fantispug »

abcdcba wrote: post #4
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

Hi Jeremy - For someone who doesn't like to watch lectures, will you guys ever be releasing a textbook?

I'm traditionally a textbook person too, but I really like fast.ai. You get to see how to tinker with things in real time (which is often clunky in a textbook), and there's a lot of informal folklore that people don't normally write in academic textbooks. If you're dead set against video you could just work through the notebooks yourself and read the referenced papers on the website.

Re: Cutting Edge Deep Learning for Coders, Part 2

#33

Post by vishvananda »

doall wrote: post #16

I watched all of the 2018 Part 1 videos and it was not my style. One thing I liked is the positive attitudes of Jeremy and Rachel, but there was not much theory and a lot of time was spent on questions and answers for the participants of the lecture that I don't think necessary. I wanted to see definitions and "why", but the course spends too much time on "how". Sometimes I see "why" in the lecture, but many times it…

I can see how The courses would be tough to digest without some theory from other sources, but I have found them to be invaluable for tips and tricks. They are loaded with practical information.

Much of Deep Learning is still experimental in nature and requires quite a bit of educated guessing. A number of times I have been stuck on a particular deep learning problem and a passing comment from one of the fast.ai videos has given me the perfect insight.

Re: Cutting Edge Deep Learning for Coders, Part 2

#34

Post by RSchaeffer »

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

Hey! Thanks for these great courses and materials! How much additional math (beyond high school and introductory college courses) do these courses teach? For example, if I were to take both courses, would I be able to understand the papers published by Surya Ganguli (e.g., The Emergence of Spectral Universality in Deep Networks, Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net)?

Re: Cutting Edge Deep Learning for Coders, Part 2

#35

Post by YeGoblynQueenne »

>> 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 have been trying to solve this devilishly hard problem for several decades and failed. So I'm really curious how fast.ai has finally manged to do it.

Re: Cutting Edge Deep Learning for Coders, Part 2

#36

Post by DrNuke »

Hi Jeremy, Thanks again to you and Dr Rachel for these amazing courses and the support to the community. My question is the following: are you thinking of an organic fast.ai connected hub or foundry acting as a distillator, that is disseminating & implementing in / with / through the fast.ai library the most interesting research papers coming out day in day out from arxiv.org and events? It is nearly impossible to follow the progress without clear state-of-the-art perspective these days, which you have in abundance indeed.

Re: Cutting Edge Deep Learning for Coders, Part 2

#37

Post by poppingtonic »

RSchaeffer wrote: post #34
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

Hey! Thanks for these great courses and materials! How much additional math (beyond high school and introductory college courses) do these courses teach? For example, if I were to take both courses, would I be able to understand the papers published by Surya Ganguli (e.g., The Emergence of Spectral Universality in Deep Networks, Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net)?

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

Re: Cutting Edge Deep Learning for Coders, Part 2

#38

Post by RSchaeffer »

poppingtonic wrote: post #37
RSchaeffer wrote: post #34

Earlier quoted context omitted.

Hey! Thanks for these great courses and materials! How much additional math (beyond high school and introductory college courses) do these courses teach? For example, if I were to take both courses, would I be able to understand the papers published by Surya Ganguli (e.g., The Emergence of Spectral Universality in Deep Networks, Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net)?

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.

Re: Cutting Edge Deep Learning for Coders, Part 2

#39

Post by bitL »

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?

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 the lecture loses efficiency. If I didn't know most of the basics already, I'd have problem following them. I found just doing the exercises better for learning.

Re: Cutting Edge Deep Learning for Coders, Part 2

#40

Post by DrNuke »

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.

You are missing the point, that is full part of their experience opening to unrepresented classes and styles. It is human together with efficient, the heart added to the mind.
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