## Natural Language Processing|TF-IDF Intuition| Text Prerocessing

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Here is a detailed discussion of the Term Frequency and Inverse Document Frequency in Natural Language Processing.

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D C says:

log base 2 or 10 ??

Vivian Data says:

You are such a talented teacher! Thanks!

A A says:

Sir now boy, girl both have equal value

StupidButCurious says:

Hi Krish, very well explained. However it still leaves me with another question. While i know this is the correct way of calculating the TF, IDF and finally the tf-IDF i still don;t understand why sklearn comes up with different tf-idf values, even with your set of examples in this tutorial
Would you help me understand

Vikram Sandu says:

Well explained. Thanks

quý vũ says:

Thank, this video help me so much. Very easily understand

alexander garcia says:

thank you so muuuuch

Pokkunuri Saikrishna Chaitanya says:

A great teacher is one who makes complex things simple. Thank you very much!!

Hi sir good afternoon my self bukke

Junaid Yousaf says:

This is really good explanation.
Sir pls make video on hate speech detection….

vaibhav gupta says:

This is awesome 💛💛💛💛🙏🙏🙏❤️❤️❤️❤️❤️❤️❤️❤️❤️

Sagar A Doshi says:

Hello Sir.. what would be tf-idf for a sentence "goodgirl" (there is no space between good and girl)

arya svn says:

Why TF IDF use log 2? What the purpose of the log 2?

Jitendra Kumar Sah says:

Thanks Krish sir….One thing sir, will that be work on any logarithm base or its work on natural logarithm which is base e or common log which have base 10?

Arjun Bali says:

thank you sir

Sruthi Parvatha says:

Thank you so much for this simple and clear explanation. Understood the concept on the first go, keep up the good work.

DIPANNITA says:

nice. cheers

Viknesh SK says:

Really great videos!!!

Excellent krish. Keep Motivating. You are doing well

Sheikh Shahbaz says:

Hey Krish M fan of ur teaching . You just teaches from very basic to advanced.

Noman Shaikh Ali says:

Where to use which NLP model like in which situation we have to use BOW and in which we have to use TF_IDF? Looking forward to hearing from you soon!!

José Costa says:

Excelent vídeo. Is there any videos where you explain how to implement TF IDF for better performance of sentiment analysis algorithms?

kalyan sundar samanta says:

This is really good explanation! How to select top words when the sample size is large? Suppose, if I select Journal Articles for the study which contain more than 5k words, then how can I select top words from them?

fantasy apart says:

sent1, sent2, sent3 should have mentioned in rows instead of in columns and in the TF formula the edenominator is total no of words in sentence instead of just no of words in sentence ..BTw good job man…

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