ML Monday live screencast: Predicting board game ratings in R

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  1. David Robinson
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0:00 - Intro, and downloading the train and test datasets and setup
4:33 - EDA (exploratory data analysis)
12:21 - Creating a linear model (glmnet)
41:40 - Creating a random forest model
1:15:38 - Using ensemble to put both models together
1:29:38 - Creating a XGBoost model
1:57:20 - Final submission, learnings and outro



Great screencast David! I learned a lot about the tuning steps while watching. Still a lot more to learn about all the different functions within the tidymodels framework.

TheDataDigest
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THANK YOU FOR THIS UESFULL SAHRING DAVID .
AS ALLWAYS TOP OF TOP

cheninitayeb
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Very Nice :) I work with tidymodel from a while and it’s nice to see different approach and tips ! A your long time fan, for me this is way better than the regular Tt

Ilproff
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It’s a pleasure to see this thought process. The xgboost tuning parameters are not what I’m familiar with. What about gamma and the two regularization parameters?

gypcasinoable