5.16 Meeting Videos

5.16.1 Cohort 1

Meeting chat log
    00:14:53    jonathan.bratt: Sorry, didn’t realize I was unmuted. :)
    00:15:03    Raymond Balise: be right back… I am listening
    00:15:16    August: time series can also be analysed with features, which means you can use decision trees, and not rely on the sequential indexing.
    00:17:08    August: for those wanting to understand when we aren't modelling on features https://otexts.com/fpp3/tscv.html
    00:17:18    August: application in modeltime https://cran.r-project.org/web/packages/modeltime.resample/vignettes/getting-started.html
    00:25:53    Jon Harmon (jonthegeek):    10-fold CV is orange, LOOCV is black dashed, true is blue.
    00:27:24    Mei Ling Soh:   How do we decide on the k-value?
    00:27:47    August: Its kind of a choice.
    00:29:05    jonathan.bratt: because we have five fingers on each hand :)
    00:29:39    Jon Harmon (jonthegeek):    rsample::vfold_cv defaults to 10 so I generally do 10 🙃
    00:29:47    August: the answer is in section 7.10.1 of ESL
    00:29:50    Mei Ling Soh:   😅
    00:30:04    August: By answer I mean explination
    00:31:09    August: With time series I tend to use about 5 or 6 k when using models which utilise sequential indexing.
    00:32:10    jonathan.bratt: Can you use the arrow keys?
    00:38:11    August: This is quite interesting: https://machinelearningmastery.com/how-to-configure-k-fold-cross-validation/
    00:39:53    Mei Ling Soh:   Thanks, August!
Meeting chat log
    00:11:39    Jon Harmon (jonthegeek):    https://twitter.com/whyRconf
    00:14:38    SriRam: go for one page view, not scrolling view
    00:25:46    Wayne Defreitas:    lol
    00:33:53    SriRam: it should be square root of mean, not mean of square root ? Or did i read it wrong?
    00:45:45    Wayne Defreitas:    This was great thank you
    00:46:27    Mei Ling Soh:   Great! Thanks
    00:49:19    jonathan.bratt: Ch6 is long

5.16.2 Cohort 2

Meeting chat log
    00:29:18    Ricardo Serrano:    https://www.statology.org/assumptions-of-logistic-regression/
    00:29:26    Ricardo Serrano:    https://towardsdatascience.com/assumptions-of-logistic-regression-clearly-explained-44d85a22b290
    01:06:18    Jim Gruman: thank you Federica!!! more horsepower 🐎
    01:07:47    Jim Gruman: I need to jump off. Talk to you all next week. Ciao
Meeting chat log
    00:18:27    Federica Gazzelloni:    Hello Jenny!
    00:18:44    jlsmith3:   Good morning!
    00:39:57    Ricardo Serrano:    References for bias/variance https://www.bmc.com/blogs/bias-variance-machine-learning/
    00:40:26    Ricardo Serrano:    https://youtu.be/EuBBz3bI-aA
    00:40:36    Federica Gazzelloni:    Thanks Ricardo!
    00:57:55    Jim Gruman: 🐎 thank you everybody!

5.16.3 Cohort 3

Meeting chat log
    00:07:07    Nilay Yönet:    https://emilhvitfeldt.github.io/ISLR-tidymodels-labs/resampling-methods.html
    00:33:41    Mei Ling Soh:   Maybe we can wrap up the lab soon?
    00:37:48    Fariborz Soroush:   👍
    01:04:24    Mei Ling Soh:   Two more minutes to go
    01:05:19    Nilay Yönet:    https://onmee.github.io/assets/docs/ISLR/Resampling-Methods.pdf
    01:05:22    Nilay Yönet:    https://waxworksmath.com/Authors/G_M/James/WWW/chapter_5.html

5.16.4 Cohort 4

Meeting chat log
00:37:41    Ronald Legere:  https://en.wikipedia.org/wiki/Bootstrapping_(statistics)
00:54:52    shamsuddeen:    Hello, I wil leave now. See you next week !
00:55:04    Sandra Muroy:   bye Sham!
00:55:13    shamsuddeen:    Thank you Sandra
Meeting chat log
00:38:01    Ronald Legere:  https://stats.stackexchange.com/

5.16.5 Cohort 5

Meeting chat log
00:03:36    Angel Feliz:    Resampling summary

https://angelfelizr.github.io/ISL-Solution-Book/resampling-methods.html
00:29:20    Angel Feliz:    https://github.com/AngelFelizR/ISL-Solution-Book
Meeting chat log
00:03:04    Ángel Féliz Ferreras:   Exercises
https://angelfelizr.github.io/ISL-Solution-Book/05-execises.html
00:03:46    Derek Sollberger:   I love this first exercise; I added it to my textbook :-)
00:18:03    Derek Sollberger:   Did you find any advantages/convenience to using the tidymodels workflows here?
00:36:34    Ángel Féliz Ferreras:   https://emilhvitfeldt.github.io/ISLR-tidymodels-labs/06-regularization.html