thanks for the video. Just a small suggestion that an "end-to-end" data science project also includes model deployment such as on a web-app, etc. I hope that your future 'end-to-end' DS project will also have this part.
@@harrysdatajourney no prob, in my opinion, long and detailed videos attract me the most since they cover the full picture,.It doesn't matter if you have long video such as more than 1 hour ^^
A question, if you have a large number of features. How do you choose between different categorical encoding? Do you attend to features on individual basis and then decide what encoding should be used?
I got this error: "All estimators should implement fit and transform, or can be 'drop' or 'passthrough' specifiers. 'Pipeline(steps=[('col_dropper', ColumnDropper(columns_to_drop=['red_vehicle']))])' (type ) doesn't." From Chatgpt, "According to the error message, the issue lies with the cols_to_drop_pipeline in the ColumnTransformer. In the ColumnTransformer, the output of cols_to_drop_pipeline should be directly discarded rather than being processed as a complete transformer." But, does anyone meet the error?
I found the typo in class: "The ColumnDropper class in this code has a spelling error; transfrom should be changed to transform. This spelling error occurs in the initial definition of the ColumnDropper class." While I correct it, all is fine. :P
I was just learning about classification models and then I got this recommendation from You tube.
Awesome video Harry.
Thanks Shailendra! Hope you found it helpful
Thanks Harry, I am looking forward for more such content from you. :)
Thanks! Let me know if you have any suggestions on what you’d like me to cover next 😀
As someone who wants to become a business insights analyst, this is very helpful. Thanks Harry! ❤
Glad you found it helpful!
thanks for the video. Just a small suggestion that an "end-to-end" data science project also includes model deployment such as on a web-app, etc. I hope that your future 'end-to-end' DS project will also have this part.
Your right! I wanted to look at covering model deployment in a separate video as this one was already quite long. Thanks for the suggestion!
@@harrysdatajourney no prob, in my opinion, long and detailed videos attract me the most since they cover the full picture,.It doesn't matter if you have long video such as more than 1 hour ^^
@@hoangha6680good to know! Thanks for the feedback 😀
Great stuff Allum
Thanks Harry!
I am Aspiring Data Scientist it's very helpful and Awesome ' ✌
great content, eagerly waiting for the deployment part.....
Stay tuned! 😀
A question, if you have a large number of features. How do you choose between different categorical encoding? Do you attend to features on individual basis and then decide what encoding should be used?
what is the name of vs code theme?
I got this error: "All estimators should implement fit and transform, or can be 'drop' or 'passthrough' specifiers. 'Pipeline(steps=[('col_dropper',
ColumnDropper(columns_to_drop=['red_vehicle']))])' (type ) doesn't." From Chatgpt, "According to the error message, the issue lies with the cols_to_drop_pipeline in the ColumnTransformer. In the ColumnTransformer, the output of cols_to_drop_pipeline should be directly discarded rather than being processed as a complete transformer." But, does anyone meet the error?
Your pipeline code looks fine. Can you share your code for the custom transformer?
I found the typo in class: "The ColumnDropper class in this code has a spelling error; transfrom should be changed to transform. This spelling error occurs in the initial definition of the ColumnDropper class." While I correct it, all is fine. :P
@@pent1162 Glad to hear it!
Are you actually typing that fast? 😮