This post is for topics related to lesson 1 of the course.
This is a wiki post - feel free to edit to add links from the lesson or other useful info which is appropriate for beginners.
Lesson 2 >>>
Links from the lesson
Other useful links
Please use this topic to ask any question about the course (even if you think they are stupid, we really love stupid questions). Note that this is the beginners topic, so if you have already followed the course and your question/intervention is more advanced, please use the
non-beginner discussion topic.
Questions with lots of likes will be asked live by John. If you see a question you’d really like to be answered, click on the heart under it to like it. Don’t post duplicate questions if possible. They will be removed by the moderators (don’t be mad if this happens to you, it’s nothing personal). If your question is not answered during the course, it will be answered on this topic after the lesson.
This topic will be
very crowded, so please refrain from getting too much off track (create another topic for this) and please like the post of someone who replied to you instead of replying with thank you.
Remember that the book
has a chapter containing details on each lesson
I think the non-beginner topic wasn’t created so I made one and updated the wiki-I hope that’s okay
A bit of OT question: is it okay if we snapshot an image of the class at some point for a social media post? Given that it’s not yet public yet, I wasn’t sure
What are the specs of your laptop that you can handle streaming, recording, and training a model
IIRC, Jeremy has Surface Book 3.
I guess he is using Windows Surface … some variant.
I was mostly curious what is the setup Jeremy has to have Jupyter notebooks as slides. I think it is this:
How to use
vision_learner to use latest computer vision models?
Pass a string of the name of the pretrained model from timm… See the example at the bottom of
I’m one of the live TA’s. If you have any issues or would like any help…please “@” me and I’ll do my best to help!
Jeremy says you learn best when you read the questionnaire first. Is this the questionnaire for lesson 1?
About & Motivation behind starting this
The motivation behind this (wiki) thread is to provide a very quick summary of the lectures + “Things Jeremy says to do”-which has been a way by which we could access Jeremy’s wisdom and suggestions from the lectures.
Note, since the lectures are not public and my hosting platform doesn’t give a method of keeping audio links unlisted, I’m not sure of the best method to share audio, so I’ll share the YouTube links and then release audio once …
To anyone that might feel a bit uncomfortable with the top down learning methods:
I had written extensively about my struggles in
“How not to do fastai”, I cover my pains of someone who studied in university-of how difficulty it was to learn something in top down fashion
We had also shared this in a “reverse” interview where Jeremy kindly
interviewed me. I hope this helps
The questionnaire is in the book. Check the fastbook repo notebooks for the Jupyter notebook versions of the book.
Here is the chapter for lesson 1:
This file has been truncated.
"! [ -e /content ] && pip install -Uqq fastbook\n",
Yes, Jeremy said the forum was overloaded at the start of the lecture.
@n-e-w is it possible to sort this page by # likes? To select questions for pushing into the lecture?
Thanks for your introduction. I saw both ‘bird.png’ and ‘bird.jpg’ in the presentation earlier. Just wanted to point it out.
Is there somewhere I can get more info on the project which used recurrence plots as input to DL? (mentioned by Jeremy in the lecture just now; I missed if there was a reference)