Lesson 6: Practical Deep Learning for Coders 2022

[@ItzGanked]

The quality of this content is unreal, thank you so much for you contribution to open education

[@JohnSmith-he5xg]

This content is sooo good. Thanks!

[@howardjeremyp]

My pleasure!

[@DeleMike7]

Thank you for the great content. Loving this lecture.

[@goutamgarai9624]

Thanks Jeremy. Great Tutorial

[@JensNyborg]

I:d like to take a moment to thank Zakia for that question about the notebooks.

[@DevashishJose]

Thank you Jeremy.

[@sportsdude2828]

Hey Jeremy, fantastic lessons. Looking forward to working through part 2! Quick question: When working with Random Forests and XGBoost regressors/classifiers, is there ever any accuracy advantage to using ordinal encoding over one-hot encoding? I realize there can be speed advantages when the number of categories in a column grows large, but if speed isn't a factor, do we even have a reason to play around with ordinal encoding? (Sorry if this was answered somewhere and I missed it!)

[@jaredwsavage]

Yes, there can be a difference in some circumstances. Ordinal encoding assumes that there is an inherent ordering to the categories which may not have any meaning in real life. For example, mapping "Bad", "Acceptable" & "Good" to 1, 2 & 3 makes sense, but mapping "Irish", "Scottish" & "Welch" to an ordinal list doesn't make much sense in most contexts. Some models will be more or less sensitive to factors like this. When in doubt, try both and see which works better.

[@lisanyaa737]

danke schon !

[@mukhtarbimurat5106]

Great, Thanks! But what if our data is biased, is random forests still good?

[@aarontube]

Jeremy, these videos are brilliant. Thank you so much for creating them. I've heard you mention the zoom walkthrough videos a few times. Are they available to watch anywhere?

[@howardjeremyp]

Yes, they're on the forum (forums.fast.ai).

[@aworden]

At about 35 mins in you jumped to some notebook that I can't find and you don't explain where it is. The written text is much clearer than the verbal explanations. It would be really helpful if your notebooks were numbered corresponding to the lessons. E.g. "Lesson 5b: Why you should use a framework"

[@18dragonface]

I believe this notebook is chapter 9 of the fast AI book

[@rjScubaSki]

Where it says Chapter 8 of the book, its now Chapter 9 I think.

[@CDolph296]

Is there a critique of this video by someone who hates random forests? Some of this seems too good to be true lol

[@maraoz]

vocab[idxs] blew my mind!