How You Should Split Your Datasets in Machine Learning

Today we learn how to split datasets in machine learning properly using the stratified shuffle split.

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[michaelmecham]

Excellent video, I didn't know the shuffle split existed. Really appreciate your expertise!

[andreasdesousa]

Thank you for this awesome video!
I had problems of index using loc so I used iloc instead and now is working like a charm!
Really appreciate.

[scurge]

started learning ml today. Few hours later your video comes out, what a coincidence

[ali-omuv]

That was a concise presentation. Nice!

[joguns]

Superb. I can say I can now split my datasets in ML.

[philip]

That's a great way! Didn't know about it. Thanks!

[Caledonia_night]

thank you! yay for more data science videos

[rahulmore]

This is a good video, simple and up to a point.

[jacksun]

Does using cut or qcut matter for situations like this?

[rahulmore]

Why not use a constant seed while splitting the dataset to make them deterministic?

[MrMadmaggot]

Dude do you think the CUT also is usefull for the X's (features)?
or maybe that's just useful when plotting or dashing in POWERbi

[miketan]

In the application of your data prep, is it true that the time series are, while splitting, are actually broken? Or are the data and test set in time order?

[amazing-graceolutomilayo]

Hi, are you just starting out learning Data Science?
And how much did you get the book?