Lesson 1 - Official topic

I tried walking into this with my Walk with fastai2 notebooks (covering the main differences in the early notebooks) :slight_smile:

Any good suggestions for tools to label images for segmentation?

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I will read that, thanks

How do we use our own dataset?

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My best experience with this has been the mid-level API, especially if your directory structure and sample files are different than the high-level use cases!

why is it called fit_one_cycle vs fit ? what is a cycle ?

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is very helpful

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Look above the discussion started by @maya :slight_smile:

We will cover that next week, but by using the docs, try to figure out how the methods grabbing the data work :slight_smile:

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Take care people! Make sure your actions “flatten the curve”.

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https://forums.fast.ai/t/lesson-1-official-topic/65626/233 and replies to it

We will learn that in a few lessons, it’s a specific kind of way of fitting, that’s all you need to know at first.

This was a great first lesson 1! Thank you Fast.ai team! So excited to continue learning together. Stay healthy all!

See you all next week! Loved this online lesson because I got to cuddle with my dog the whole time :joy:

Thanks @rachel and @jeremy for another great session, course, and library version!

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For those of you wanting to run the graphviz code in the notebooks (and you are doing so on your own linux box) … do this:

sudo apt-get install graphviz
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fit is more for the same hyper parameters (settings for training) over time. fit_one_cycle changes these over time.

Thank you very much Rachel & Jeremy :slight_smile: and Sylvain and others :slight_smile:

The “one cycle” policy is something that Sylvain, Leslie, Jeremy, and other Fastai folks empirically determined to be a way to rapidly train a deep learning model. See Sylvain’s blog post: https://sgugger.github.io/the-1cycle-policy.html

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THANK YOU SO MUCH , great first lesson

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