Effective Resampling for Machine Learning in Tidymodels {rsample} R package reviews

In this video, we'll learn how to use three most important resampling techniques: train-test split, cross-validation and bootstrapping. Random sampling, stratified sampling for numeric and categorical variables. What is not in the video are grouped resampling and time specific resampling, they deserve a separate video each.

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Enjoy! 🥳

Welcome to my VLOG! My name is Yury Zablotski & I love to use R for Data Science = "yuzaR Data Science" ;)

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[hansmeiser]

I am watching R-tutorials since 7 years now. Your visual representations and explanations are the *best, * I've ever seen- so far.

[muhammedhadedy]

What I love the most about this YouTube channel, is that the quality of the free tutorials is much better than many paid ones. I must admit, that you have a talent in illustrating such a complex topic into very easy method. A true professor you are. I really don't know how to thank you.
I would be so grateful if you create a tutorial of machine learning using tidymodels package.
From the bottom of my heart, thank you.
❤❤❤❤

[aiz_i]

Thank you! It helped me a loot! Excellent explanation!

[wbdill]

Even though I know very little about modeling it is clear that this package kicks ass! The animations on this video illustrating the concepts being described is superb!

[SUNILYADAV-tvze]

Nice lecture for resampling. Please make a video for simulation study

Excelent! Great animations and clear explanations. Thanks!

[rodrigonehara]

Incredibly usefull chanel, love your work.

[joshstat]

Thanks for the vid sir. Can you create a video about the use of tidymodels in time series model and analysis?

[abdulmusa]

Kudos to our Boss, thanks in million sir, the data scientist gurus in the universe
Sir could you make a tutorial on handling class imbalance when dealing with a binary classification

[chacmool]

Good to know about Monte Carlo CV in that package. Where does Monte Carlo fit in the variance|bias continuum vis-a-vis bootstrapping and cross-fold validation?

I use tend to use 'caret' instead where I dial in these model performance tests via train_control.

We need a vid on sub-space clustering. 😉

[AnimeshSharma]

Very well explained 👍 Thanks for sharing 🙏 just to be clear, for cross-validation, which model is going to run over the test-data created in the very beginning?

[yurisilvadesouza]

Could I use this approach to remove some BIAS regarding different data sample efforts? Example: I have a dataset with monthly video records of animal interactions with vertebrate latrines. However, some spots have different months' recordings because come latrines weren't there when I installed my equipment, meaning I have different latrines sampling with different sample efforts. I am looking for a way to correct it, but since stats are something new for me, I was wondering if this approach you use could be used in my situation.

Please don't stop doing this, we need this kind of informative videos and didactic 🙏🙏🙏. Thank you again for this one!

[samirhajiyev]

13.25 you have used rand_forest() instead of lm() on code line 124. Could you please clarify?

[mohamedaddani]

Hello. Can you do a demo about how to do bootstrap in R. Also the website link is not working. Thank you

[galan]

Regarding this, yuzaR, I was wondering if it existed something along the concept of keeping % of classes in our test-train split, but for numerical values in order to draw two populations that got the most similar means, sd and all of that. Thank you :D

[serhatakay]

So how can we use cv sampled or bootstrapped models in prediction using predefined test set?