Great lecture thanks @jeremy! Does anyone know if there is a significant difference between the book via fastbook notebooks and the ebook version? I do like to read in bed with my kindle, so just wondering if I should preference the new notebooks over the 2020 book for any reason?
They’re identical content - the book just has some nicer formatting.
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The slides are in the Kaggle notebooks linked in the top post of this thread.
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You’ve misremembered a bit there! DataBunch was renamed to DataLoaders. DataBlock isn’t much related to a Dataset. It’s a builder for DataLoaders.
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Is it a bird? Is is a plane? IT’S SUPERMAN!!!
Taking a cue from Jeremy’s notebook shown in today’s lecture, I tweaked it a bit to classify images into three types.
Over the week, I am planning to annotate it with my thoughts and explanations. Posting this here to keep myself accountable! The notebook is just barebones atm.
It was fun to do this so a big thank you to Jeremy and the fast.ai team!!
Also, we dont have a share-your-work topic for this iteration of the course. Maybe that can be created and posts such as these could go there?
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Just wanting to confirm… at fast.ai Live - Lesson 1 - YouTube
when Jeremy says “If you are watching this video right now on youtube, I strongly head over to course.fast.ai and watch it there instead”, is that an example of what was mentioned earlier as being related to after public release? I presume this content is not yet there.
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Yes .
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Correct.
Sure that’s fine. Thanks for checking!
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It’s a Surface Studio Laptop. I’m really happy with it - great computer!
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Except that I’ve got 4 new-ish kernels that (hopefully) are on their way to gold medals already! 
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One thing that I don’t like: highly reflective screen.
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Admins, please delete or move this reply if it’s not appropriate for this thread
Jeremy wears a mask, no matter being alone at the podium. Just to say that I’m glad to see that someone still takes the matter of wearing masks seriously.
In Europe, since the onset of the war, people no longer seem to care about covid and associated precautions. And that’s just stupid. We are still having 300 deaths per day, on average, in my country.
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Completely agree.
I am in Belgium.
COVID has just “vanished”.
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I started my fastai adventure with v1. Thrilled to be back! In addition to re-engaging with deep learning, this time around I want to study the design of the fastai software more closely. In browsing through the source code, I discover so many interesting techniques, not just specific to python, but to programming in general. It’s a real pleasure to review such beautiful code. @jeremy, @sgugger and everyone else involved deserve a ton of credit!
An amazing example is: L, a drop-in replacement for List. I’m a long time user of lispy languages and L allows for a much more functional approach to python programming. It really should be a part of core python. I plan on using it in my non-fastai python coding.
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Hi all,
I have a general question, please.
Is it possible to use the fast.ai library to train a model if you only have for example, a positive labeled dataset (and there is No negative dataset)?
But then, still use the trained model above, to thereafter test any similar data (could be either positive or negative)?
Is the above possible? Or any other pertinent information will be appreciated.
Thanks in advance.
Kind Regards,
Zakia
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