Scikit-Learn Model Pipeline Tutorial

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Thanks Greg. This made me realise how non-standard my code is.
I learnt:
- Use copy or deepcopy and not assignment.
- Always perform preprocessing on the train and test separately.
- sklearn pipelines have nothing to do with ETL pipelines from Data Engineering.
- sklearn transfers have nothing to do with NLP Transformers.
- sk elarn estimators have nothing to do with Statistics estimators.

TheCsePower

Keep Posting Greg, I am Data Analyst by profession and your video certainly helps a lot

crepantherx

Great stuff! I’m curious why you used FunctionTransformer instead of ColumnTransformer, which could run the two scalers in parallel? Also, since FunctionTransformer is stateless, the documentation says that fit just checks the input rather than actually fitting the scaling parameters. Doesn’t that lead to data leakage since applying transform to test data won’t use parameters learned from fitting on the training data?

hansenmarc

thanks, Greg. really good explanation and structured example. this makes it easy to create a template for easy reuse!

kyleGrealis

A very practical video, that I came across on Pipelines. Thank you for this video!

AmitabhSuman

When you do the StandardScaler().fit on the dataframe, what is the meaning of this operation? what is happening?

ilanyutsis

I undstand what you are doing here but I have two questions that I think would be helpful and would make it easier to follow along and replicate you steps.

1) Where did you get the data. I can't the california_housing dataset that is already in the train/test form.

2) Why not use scikit-learn tooling rather than doing it yourself? Like you could have used train/test split or pipelines (or column transformer... or similar stuff). That just has me confused.

alexrook

I would love to see a tutorial that covers using pipelines with multilayer perceptron models (MLPs), CNNs and LSTMS.

JJGhostHunters

Great tutorial! I use the MinMaxScaler with the option to scale from -1 to 1 instead of 0 to 1 when I am dealing with values that can be positive and negative. Seems to be fine, but I may need to reconsider going forward. I have never noticed any issues though.

JJGhostHunters

Just out of curiosity, is there a reason you don't use train_test_split to get X and y values?

brandonn

Thank you Greg! It's a great video!

lythien

Thanks for the great tutorial. Can you make a video on how to combine multiple feature selection methods and feature extraction using python?

Nadia-dbnb

Thanks for this amazing video! Would that work also with a statsmodels model?

TheFrankyguitar

How to transform y variable and then fit model. And after how to reverse transform for the scatter plotting

junaidlatif

Thanks for the great tutorial! what do I need to change to create a pipeline for an image classification model? like the cifar10 model?

talyb

Did you say pipelines doesn't function for classifications problems? Min: 1:07

fabioful

Bro can you show how to make youtube and any video downloader make by python

tareq

Bro you literally just copied this out of a textbook lmao but I respect the grind.

AceOnBase

Too confusing. Too many tangents, doesn't cover the main idea clearly. Downvoted.

johnspivack

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