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How to EASILY get the BEST Machine Learning Model with PyCaret (PyCarrot?) - AutoML in Python

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Опубликовано:

28 авг 2024

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Комментарии : 36

@GregHogg Год назад

Take my courses at mlnow.ai/!

@Value_Pilgrim 2 года назад

Coming here after a long time. Found this very, very interesting. Thanks.

@GregHogg 2 года назад

Welcome back!

@superfreiheit1 2 месяца назад

Great video and a great packet. It would be great to have a build in hyperparameter tuning in carets

@elizabethmorales9469 2 года назад

I think this channel is really cool thank you for your knowledge!

@GregHogg 2 года назад

I really appreciate that Elizabeth!

@mikekertser5384 2 года назад

Thank you. It is very nice indeed, but seems to perform slowly on a large datasets, at least without GPU support. Saving the blended finalized models may result in surprisingly large files.

@GregHogg 2 года назад

Hey Mike! Yeah, luckily they said it should be much faster with a GPU. On a cluster I'm sure it'll be good, although personal computers wouldn't have access to that

@TS-fp5xg 2 года назад

well explained ,thank you so much

@GregHogg 2 года назад

Great to hear, you're very welcome!

@pramishprakash Год назад

Sooper cool... Thanks alot sir

@FaroukYahaya-xi4ri 3 месяца назад

what if i dont want to use the best model. but i want to select a particular model. so how do we change the print(best) to that specific model and finalize?

@rgoudie Год назад

Great stuff, Greg. Can you make a video on how to use PyCaret with time series? I am particularly interested in time series classification. Thanks.

@GregHogg Год назад

Hey Ray! Yeah that's on my to-do list for sure.

@arsheyajain7055 2 года назад

Ooh amazing!

@GregHogg 2 года назад

Thank you!

@mkvalor 10 месяцев назад

Great content. My immediate question is whether this framework works well for time series data which cannot be randomly shuffled, since it seems to do a lot of folding and cross validation on its own. Do you know if it has good options to keep the data ordered while still maintaining the ability to choose the best models?

@Mike-vj8do 6 месяцев назад

Hey bro, I really love the video. I'm wondering whether you think this automated ML engineers' jobs? Thank you very much.

@GregHogg 6 месяцев назад

It definitely helps ML engineers. And glad to hear it!!

@jacktrainer4387 Год назад

pyCaret took 2 hours and 53 minutes to train lgbm, gbm, and a dummy model on Google Colab Pro Plus (yes, the big guns). I could have done the models with pen and paper faster. You should have mentioned this in your video.

@hivinline5184 Год назад

i'm sorry, i am new at this. i already use my own dataset for this, but it's doesn't work. even tho i already do many processing with that dataset. is it some thing wrong with the dataset or the pycaret can only do its own dataset? (sorry english is not my first language)

@SP-db6sh Год назад

Thank you. Plz Video on training DL model using Pycaret GPU

@ytshortsgenerator Год назад

another 🔥

@ytshortsgenerator Год назад

Can I use this with CNN?

@GregHogg Год назад

Glad to hear it, and there's definitely some automated CNN libraries

@imveryhungry112 Год назад

is there one for finding best nueral network model?

@librae-5664 2 года назад

thanks a lot!! one questions, how to edit n_estimators hyperparameters of base model?

@GregHogg 2 года назад

You can use the create_model function. Check the docs :)

@patricionovellino6793 2 года назад

Hi greg. Amazing video! I am going to try it with my actual and first project. What environment do you recommend(colab or jupyter)? Given the fact my dataset has 780k rows

@GregHogg 2 года назад

For 780k rows, you might need a cluster. Colab definitely won't work

@motaseamyousef7668 2 года назад

OMG! better than grid search 😂😂😂

@GregHogg 2 года назад

Haha yup!

@nataliaresende1121 2 года назад

Do you know any similar approach to get the best neural network model?

@GregHogg 2 года назад

Yes, I made something similar for tensorflow recently. Also, pycaret will consider neural networks since basic feed forward nets are included in sklearn.