---
date: "2024-10-09T17:33:47.000Z"
title: "2024-10-09"
tags: ["course.fast.ai"]
draft: false
---

Some quotes from Lesson 3 of course.fast.ai by Jeremy Howard.

> I remember a few years ago when I said something like this in a class somebody on the forum was like "this reminds me of that thing about how to draw an owl".
> Jeremy's basically saying okay step one draw two circles, step two draw the rest of the owl.
> The thing I find I have a lot of trouble explaining to students is when it comes to deep learning, there's nothing between these two steps.
> When you have ReLUs getting added together and gradient descent to optimize the parameters and samples of inputs and of what you want, the computer draws the owl.
> That's it.

> I pretty much only use resnet18 at the start of a new project because I want to spend all of my time trying things out.
> I'm going to try different data augmentation, I'm going to try different ways of cleaning the data, I'm going to try to bring in external data, and so I want to be trying lots of things and I want to be able to try it as fast as possible.
> Trying better architectures is the very last thing that I do.

> My very strong opinion is that the vast majority of projects I see in industry wait far too long before they train their first model.
> You know in my opinion you want to train your first model on day one with whatever CSV files or whatever that you can hack together.
> And you might be surprised that none of the fancy stuff you're thinking of doing is necessary because you already have a good enough accuracy for what you need.
> Or you might find quite the opposite you might find that oh my god we're basically getting no accuracy at all maybe it's impossible.
> These are things you want to know at the start.