Hello, fellow coders!
I finished Lesson 1: Deep Learning 2019 - Image classification! Thank you, thank you, please hold your applause.
Postmortem
No surprise, fast.ai did the lesson well, and I appreciate Mr. Howard’s plain teaching style. I’ve had unnecessarily pedantic teachers that get in the way of learning. I think there’s a place for both teaching styles, for an intro course though Mr. Howard nails it. It’s refreshing to learn an advanced topic with applications first then theory. It boosts my motivation. My only feedback is to maybe record with a better microphone for v4. Sometimes when Mr. Howard says the letter “s,” it spikes the volume and makes it harder to listen with loud volume, which is important to me because I’m a little deaf.
You do a great job of framing the rapid progress in the field! It’s incredible how we can beat the state-of-the-art breed classification for dogs and casts from less than a decade ago with a few code lines. I’m excited about further lessons!
For homework, I want to build my classifier, any dataset suggestions?
Follow-up Questions
- When I run the code today, I get this warning on many of the output cells, including fitting one cycle:
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2854: UserWarning: The default behavior for interpolate/upsample with float scale_factor will change in 1.6.0 to align with other frameworks/libraries, and use scale_factor directly, instead of relying on the computed output size. If you wish to keep the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details.
warnings.warn("The default behavior for interpolate/upsample with float scale_factor will change "
I’m running the code on Google Colab, with the latest version of
!curl -s https://course.fast.ai/setup/colab | bash
It mentions to set recompute_scale_factor=True
to keep old behavior, yet I can’t find that as a paremeter of the function fit_one_cycle()
.
Does anyone else have this warning, and is there any way to disable it? Please, my notebook is filled with these warnings!
- May someone smarter than me please explain
r'/([^/]+)_\d+.jpg$'
?
I’ve studied the basics of regex expressions, but I can’t figure out how this code works. Individually, what does [^/]+ do? I know the + means one or more of the brackets, thus does it mean to match the start of the subgroup to start with /? I also don’t understand what the brackets do here. I tried designing my regex with the modifiers /(.*) to grab any character after the /, but it predictably catches the whole path, not just the end. Thanks for the help!