Lesson 3 In-Class Discussion ✅

Questions about nlp Imdb notebook
1- Let’s say I have already prepared train and valid datasets? how to pass them to tokenizer/numericalizer?
2- How to set a different language to the Tokenizer? Like lang=”pt”?

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version 1.0.21

It is updated with ImageDeleter function

https://forums.fast.ai/t/lesson-2-further-discussion/28706/62?u=win

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Is there a repo to contribute to http://videos.fast.ai/?

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Password is deeplearningSF2018 (do not share outside the forum group)

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Is there a suggested way to to prediction on batches of images? Not from the web but just scripted?

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But I think @rrmphal is looking for a code repo to contribute.

Is the recommendation for Andrew Ng’s original Coursera course or the new @ deeplearning.ai or both?

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The original one

PRs welcome: https://github.com/zcaceres/fastai-video-browser

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The fastai ML course covers random forest in detail…can we expect ML part2 covering GBMs?

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Good resources re: deployment in general (for beginners)?

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I have done both the courses. But I felt it to be more theoretical and I was not confident enough to dive into dive into Deep Learning coding as opposed to this course. But I think it was also a great course to get deeper knowledge

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I think doing a simple Flask tutorial would be helpful for understanding deployment: http://flask.pocoo.org/docs/1.0/quickstart/

Once you see how to set up a simple webserver that replies with “hello world”, you’ll just need to adapt for response that returns your model prediction. Here’s my example

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Anyone have resources for how to get started using video? (i.e. pulling frames from a video and submitting those to a model?)

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I made a post earlier this year before V1 came out and didn’t get much traction. I would love to train a model and build an app to play the game Set. It’s a fantastic card game and even Peter Norvig did an analysis of it.

Anybody want to form a team? I think the hardest part of this will be the dataset. I’m not in a study group at this point as I’m remote and kind of alone in my city.

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Where to find today’s class slides?

Can we set how many augmentation we apply for one image in epoch?

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I write a short tutorial to use kaggle API in google colab. It may help

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Getting a bunch of errors. E.g., in Config.data_path()/'planet', it’s saying that Config doesn’t have data_path attribute. Similarly

src = (ImageFileList.from_folder(path)            
       .label_from_csv('train_v2.csv', sep=' ', folder='train-jpg', suffix='.jpg')  
       .random_split_by_pct(0.2))

fails with

TypeError: datasets() missing 1 required positional argument: 'dataset_cls'

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