Part 1, online study group

Part 1 (2019)
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Hi all. I am also interested to join the group. I have started some time ago and just posted my first toy project at share-your-work-here-thread and the respective notebook is available at my github. Looking forward.

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Thanks @jeremy for supporting this little community! It means a lot!

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Good to know @Miske :heart_eyes:

Great work @dmilush ! It would be great if you could show your project during the next meetup :smiley:

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There is NLP study group starting here :star_struck:

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Hello Deep Learners! Just a reminder, we are having a meetup today at 3PM GMT, that is in 35 minutes! There is a new link to join meet.google.com/hsk-jdtn-znq.

Looking forward to the meeting :hugs:

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@shahnoza Is everything working alright? Currently I am to get my request to join approved.

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There were technical difficulties using the google meetings. Here is the link to the zoom meeting:

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New link for today :slight_smile: https://zoom.us/j/707007288?pwd=V01LNUg1MDI2Q2IyRkpKK3IvbjlDQT09

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The newest one: https://zoom.us/j/667960772?pwd=d2tKK1JjdzVqeGVSRGYwbmdlRXJodz09

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Are there such groups but offline?

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If you don’t have one in your area (Chances are you might)-That’s a great point to start one.

That’s what I did too :tea:

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You can also check in meetup app or facebook groups. I was able to find one through meetup in my place last year.

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What lecture are you on now? I would like to join.

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People are mostly in Lectures 1, 2, 3,4. During the meetup everyone gives a short summary about the progress they have made during the week (lecture, personal project or group project) and we discuss interesting points. So different lectures get covered. Which lecture are you doing now?

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I would like to join, just finished watching lecture 1 and part of lecture 2 on YouTube. My time in front of a computer is limited outside of work, so it would be nice to be in a group so I can push myself.

I just got done building a PC with a GPU (1060 GTX) so I can run some DL. Currently it has Windows 10 pro and I was going to install pycharm, Anaconda and Pytorch. I’ve got both a 512 GB and a 1TB NVMe drive. I’d like to save $ and use that system for this course if at all possible. If someone could message me about what’s a good set of instructions for that. Otherwise I’m going to assume I need to use one of the server services mentioned in the course.

My education is as a physicist but my day job is a control systems engineer. I’ve got a few specific domains I’m interested in applying DL to.

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Sounds great! I use Google Collab, because it is free and it’s GPU is enough for practising first lessons :slightly_smiling_face: What domains are you interested in?

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There is a meetup today at 3PM GMT.

Join Zoom Meeting:
https://zoom.us/j/226775879

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The meetup is on =)

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Meeting Minutes (14/12/2019)

  • Participants shared & discussed their Kaggle Kernel submission for Kannada MNIST competition along with Q&A
  • Discussion about lesson 1-pets

Advice

  • Make it work and try to make the first submission before shooting for higher scores.
  • Optimize for iterating faster so that you can test your ideas quickly.

Common mistakes to avoid for Kannada MNIST

Databunch creation

  • Not setting the batch size
  • Not setting the normalize part to imagenet_stats when you are using pretrained model
  • Not setting the random seed

Model

  • Start with the simplest model like restnet18, resnet34 if you are using pretrained models before trying with larger models.

Evaluation

  • learn.recorder.plot(suggestion=True) after learn.lr_find for setting the learning rate.
  • Train a bit longer (increase the epochs) if the training loss is much higher than the validation loss

Resources

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Hello,

Great initiative! I would love to join next week. Could you please send me an invite?

Thanks!

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