Multinomial Naive Bayes Using Python | Text Classification Using Naive Bayes |

The explanation was Awesome just make one correction @10.20 you said that label encoding means converting text data into numerical. basically it's word embedding. label encoding means converting categorical data to numeric.

can I get this dataset from anywhere?

Great, thanka a lot ma'am 🤗🤗 can i ask to you, what if i want to show xtest result after tf-idf ma'am? I have tried only with the xtest code but the results are not as desired

Pls is there a github link for this video
If so...

Great video, thanks for taking the time creating it

Thanks for the clear explanation mam, but mam from where we get dataset of this model you used in this video

mam can u plz share that csv file?

how to use the attribute feature_log_prob_ in MNB. please reply

Hey Aarohi, can you provide me with the link for the sample dataset you are using?

What if we don't have category column in our table, and just have the contiments?? how will we implement such model?

Hello

I have a question. The data set that you used was for training, which one did you use for predictions? Or am I missing something?

Thanks !

Nice video! Just wondering why the shape of title_tfidf is (77,257), in the video it just seems like a shape with far more than 77 instances (because there are multiple words in each setence) and only 2 features --- the (*,*) and a decimal number.

Great! step by step Clear Explanation ..... this helped alot

Thank you so much exactly what i was searching for .

Very helpfull thank you so much, you are doing good job, please keep it up

Hi I’m having trouble with one part of the coding could you help me.

I want dataset for multinomial classifier from where i download data set??

Good Work ❤😍

Ma'am I'hv been following this video through out my minor project of 7th sem. Now I am stuck at the last phase.. I'hv trained the model and save it using pickle . And while loading it in other python file and use for prediction . It shows "Raise value: Dimension mismatch error" . Kindly help.