Machine Learning Model Deployment using Flask | Flask RESTFUL API

[@Erickeagle16]

Nice video sir😃 all the concepts are fully explained....

[@SatyajitPattnaik]

Hopefully 👍

[@posh1718]

Good class!

[@rohitbhapkar4352]

Great video ! helped me a lot

[@shreyjain6447]

What if i have categorical features in my model? Sure I would encode them but what changes should be made in the production code so that it accepts strings as an entry?

[@SatyajitPattnaik]

It takes string as an entry, but in your code it would be transformed before calling the model.predict()

[@abhishekprakash9803]

@@SatyajitPattnaik only you focus on integrer what about inputs as a categorical variable........

[@SatyajitPattnaik]

@@abhishekprakash9803 I can make a more advanced deployment soon 😎

[@manjulasrihari4485]

Super

[@SatyajitPattnaik]

Thanks

[@gurpreetkaur-pd8ne]

Where did the flask application is being created. Please help in understanding.

[@gurpreetkaur-pd8ne]

Hi!!! Could you please help me in understanding that where did you write the flask code ??

[@armaandeep9293]

He wrote it in an IDE like vscode but some older IDE i guess

[@elijahnkuah1999]

thank you very much for the educative video. Much grateful. Please i will be glad if you can share your home.html file

[@SatyajitPattnaik]

Link is already in the video description: github.com/beingdatum/BreastCancerPrediction
Go to templates folder..

[@prabhurajdhondge5779]

I am not getting any http link after debugging

[@gururajkotian8406]

Hello sir, I have gone through your tutorials, its amazing. I need your help sir. Currently am working on customer segmentation for my ecommerce app. Thing is I know how to cluster and all but don't know how to deploy it to my app. Can you help me in this ?.Do you have any tutorial on customer segmentation ?

[@thirumalaisurya1136]

hi bro , plz can you make again without using HTML and CSS ...because i need to deploy using only flask API ..no need html

[@SatyajitPattnaik]

Whats the advantage of doing it ?

[@GAZFLAIR3D]

if __name__ == "__main__":
app.run()