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Deep Learning for Coders – Launching Deep Learning Part 2

fast.ai

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Re: Deep Learning for Coders – Launching Deep Learning Part 2

#21

Post by metafunctor »

jacquesm wrote: post #16
jph00 wrote: post #13

Earlier quoted context omitted.

There's a docker image available : https://github.com/deeprig/fastai-course-1 . This is from the same excellent person who created http://crestle.com , which has all the notebooks and data files for the course pre-installed. (You can also install everything locally using the setup scripts available on the course github repo.)

It might be worth it to do an updated version of course #1 at some point, many of the examples will not work now if you try to follow along with the video because libraries (for example Keras) have been changed or upgraded. (I know you have plenty to do, so really no pressure, this is simply a nice to have for newcomers that 'tuned in late'.)

Earlier this year, the lessons stopped working for a while because the setup scripts ended up installing Keras 2, but the code was built for Keras 1.2. I was bitten by this in March, but I've been told everything works fine now (the setup scripts now use Keras 1.2 specifically).

Upgrading the lessons to Keras 2 is of course nice; I wonder if the videos will need to be re-recorded for that?

Re: Deep Learning for Coders – Launching Deep Learning Part 2

#22

Post by leesec »

jph00 wrote: post #17
jacquesm wrote: post #16

Earlier quoted context omitted.

It might be worth it to do an updated version of course #1 at some point, many of the examples will not work now if you try to follow along with the video because libraries (for example Keras) have been changed or upgraded. (I know you have plenty to do, so really no pressure, this is simply a nice to have for newcomers that 'tuned in late'.)

Yup we're starting it in October! :) (Although if folks follow the course and use the AMI or setup scripts provided, all the correct versions will be installed automatically still today.)

Hi Jeremy,

Recently started the first course and wanted to say I am really loving it. Thank you and Rachel for your time and effort into making this topic more accessible.

Getting things set up for lesson 1/2 I noticed there were a few confusing hiccups along the way, I was wondering how do I get access to edit the wikipedia to smooth out a few issues I struggled with?

The forums are generally helpful but it's a lot to wade through and overwhelming for newer participants.

Re: Deep Learning for Coders – Launching Deep Learning Part 2

#23

Post by jph00 »

jph00 wrote: post #17
jacquesm wrote: post #16

Earlier quoted context omitted.

It might be worth it to do an updated version of course #1 at some point, many of the examples will not work now if you try to follow along with the video because libraries (for example Keras) have been changed or upgraded. (I know you have plenty to do, so really no pressure, this is simply a nice to have for newcomers that 'tuned in late'.)

Yup we're starting it in October! :) (Although if folks follow the course and use the AMI or setup scripts provided, all the correct versions will be installed automatically still today.)

You can PM me through the forums to get a wiki login.

Re: Deep Learning for Coders – Launching Deep Learning Part 2

#24

Post by metafunctor »

Part 1 was great.

However, the first lesson took a bit of stamina to go through. Much of it was introducing basic Unix/AWS/shell/Python things I know intimately and have strong opinions and deeply set ways about. Shell aliases, how to use AWS, what Python distribution to run, running Python from some crazy web tool called notebooks (and not Emacs), etc. felt like I was forced to learn a random selection of randomly flavored tools for no good reason.

Yes, it's a random selection of tools. The good reason to bear them is that you'll learn how to implement state of the art deep learning solutions for a lot of common problems.

So, I ended up viewing the lessons not as "this is how you should do it", but rather as "here's one way to do it". And it does get much easier after internalizing the tools in Lesson 1.

Just something to keep in mind when branding this as "deep learning for coders". Coders have deep opinions about the tools they use :)

Re: Deep Learning for Coders – Launching Deep Learning Part 2

#25

Post by daedalus13 »

jph00 wrote: post #10
jph00 wrote: post #7

Earlier quoted context omitted.

The move from platform.ai to files.fast.ai could have been communicated better - sorry this impacted you. (We tried to highlight everywhere we could, but we can't change the video itself on YouTube unfortunately.) We're redoing the whole of part 1 starting in October so this problem will be fully resolved then. Until then, follow the links on course.fast.ai or the forums, rather than what you see in the part 1 videos…

Oh and about the teaching philosophy video - until we posted that we had quite a few students express confusion about the top-down approach. After posting it, we've received a lot of positive feedback about it. I understand it's not helpful or interesting to everyone, but overall it seems to have been a successful addition for most.

I like the philosophy and I liked that you communicated it. I think you could have communicated it much more simply & compactly. I suggest you either hire an editor or take an editorial perspective to your content for the redo of part 1. The former is better than the latter because they will benefit from having a different perspective to you and might be able to give feedback that you haven't considered.

Re: Deep Learning for Coders – Launching Deep Learning Part 2

#28

Post by learner101 »

metafunctor wrote: post #24

Part 1 was great. However, the first lesson took a bit of stamina to go through. Much of it was introducing basic Unix/AWS/shell/Python things I know intimately and have strong opinions and deeply set ways about. Shell aliases, how to use AWS, what Python distribution to run, running Python from some crazy web tool called notebooks (and not Emacs), etc. felt like I was forced to learn a random selection of randomly f…

I come from the opposite side of the spectrum. I know nothing about UNIX/AWS/Shell and have no intimate or strong opinions on any of the tools. I am confused by basics such as how to make a special request for P2 access, since the set up video is out of date. The git cloning recommendations on the wiki is also confusing to me. I'd rather see a video on how to do the git cloning or step-by-step instructions (with pictures) on how to do this and what to expect if it has been properly done.

I felt like some of the material is outdated and I find it not clear how to get around it. I ended up getting frustrated with the set up videos and git cloning instructions, so I skipped it in their entirety. I hope the future iterations of this class spell things out for beginners like me. Otherwise, I can't even begin the class since I don't know how to request access to P2, clone git, etc.

I am not uneducated. I come from a pure mathematics background and don't know anything about this set up business. I can code, know theoretical CS, but when it comes to setting up the tools (along with the outdated material) I am utterly lost.

At this point I'm just watching the videos. I can't actually do any of the coding stuff since I don't have the tools set up, but I like their top-down approach and am learning a lot despite these obstacles.

Re: Deep Learning for Coders – Launching Deep Learning Part 2

#30

Post by metafunctor »

learner101 wrote: post #28
metafunctor wrote: post #24

Part 1 was great. However, the first lesson took a bit of stamina to go through. Much of it was introducing basic Unix/AWS/shell/Python things I know intimately and have strong opinions and deeply set ways about. Shell aliases, how to use AWS, what Python distribution to run, running Python from some crazy web tool called notebooks (and not Emacs), etc. felt like I was forced to learn a random selection of randomly f…

I come from the opposite side of the spectrum. I know nothing about UNIX/AWS/Shell and have no intimate or strong opinions on any of the tools. I am confused by basics such as how to make a special request for P2 access, since the set up video is out of date. The git cloning recommendations on the wiki is also confusing to me. I'd rather see a video on how to do the git cloning or step-by-step instructions (with pict…

Most of the time I also ended up just watching the videos, picked up the concepts I didn't yet know about, and experimented on them in my own way. I did perform all the Kaggle submissions, though, to kind of calibrate my level.

I wonder how big the crowd between our two extremes is — the people who actually do run the commands exactly as explained in the videos? If the material is outdated, beginners cannot. Experts will do their own thing. How many people will follow the actual instructions?

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