This is one of the legendary videos I have seen. I’m into SEO and trying to wrap my head around semantic SEO. Some experts in the semantic SEO industry use technical jargons and fail to explain how semantics engines like Google work. But your series helped me understand every single bit of it. I don’t know python coding, but now I understand how Google algorithms work to rank any document. I understand the type of computation they do behind the screen. The video is pure gold! I mean it! This helps me as a search engine optimiser and makes me better understand machine and human interaction. Thank you so much 🙏 ☺️

oh bhai.. unbelievable... 2hrs of content......genuinely dil se shukriya sir appko....

This playlist is necessary for basic to advanced NLP engineers. Please do upload the complete series Sir. Your contribution is life saving.

Please carryon this series and we would like to learn advance NLP using deep learning/langauge models,sota techniques once basic NLP is done.

Huge respect sir, You deserve more than million followers. Love from Nepal ❤️❤️❤️❤️

I was confused to select word embedding technique for my fyp project and found this video life saving. Thank youu soo muchh !!!

I cannot find any reason not to like this video. It's amazing!

thank you so much. you explain the concept in a very very simple way. once again thank u so much 🙂🙂🙂🙂

For me You are the best data science teacher. ❤❤❤❤❤

Respect for your hardwork

Superb explanations !

Thanku so much sir for a wonderful explaination. Hatts off to u always!

Almost 2 hours...Respect!

the best tutorial i found from you.

It was awesome .. love you sir... thanx for your efforts

Best series on NLP

Thank you for another great session

Your explanation is so great!! Vo bhi hindi me. Thanks a lot!!💙

Bohot tutorials dekha but aap best ho sir

I am following your Ml playlist sir you have great explanation, sir please complete xgboost and DBSCAN algorithm in this playlist and please start series on Deep learning..

@AkashBhandwalkar

2 жыл бұрын

I'm following it as well

@campusx-official

2 жыл бұрын

Will do it in January

@AkashBhandwalkar

2 жыл бұрын

@@campusx-official woaahhh! Thank you sooooo much! This made my day! 🥳🥳🥳

@749srobin

2 жыл бұрын

@@campusx-official which year january sir ?

@debojitmandal8670

Жыл бұрын

@@campusx-official hi sir based on your example using tri gram the vocabulary is decreasing to 5 so i dont follow your this part when u said the vocabulary increases as the n gram increases

Teaching style awesome... Go ahead.

Thank you sir...Really itne easy way me smjhane ke liye

Sir..thank you for the wonderful video

Awesome content and explanation sir 👐

awesome video

This channel is highly underrated...

Thank you very much Nitish sir!

Appreciate your efforts

Incredibile ❤️

Congratulations sir for 10K Subscribers.

THANKYOU SIR

Great Video Sir.

KUDOS TO YOU SIR ..............loving this series

Thanks a lot Sir. My Phd is on NLP only .your videos helps me a lot in understanding overall concepts . Your efforts are very sincere and dedicated 💯

@forgotabhi

5 ай бұрын

I am getting started with NLP :) I am still doing my UG can you tell me your experience in the field?

@HarshVardhan-jj9xh

5 ай бұрын

@@forgotabhi Its amazing field and day by day u will came to know new models and architectures.

@hritikroshanmishra3630

3 ай бұрын

@@forgotabhi which college?

wow , after watching this video, I am confident on feature engineering

Congratulations on 36K subs, soon we gonna cross 100K IA :)

Congratulation for 100K subscribers in advance.

i love the way sir explains, i am not able to grasp the fundamental concepts but not able to imagine myself to code for NLP without any guidance ,Any suggestions what other materials and sources I should follow ?

Very good flow sir . Kindly upload next in NLP series

Amazing video

Thank you🌹

at 55:24 , BOW doesn't consider the sequence of sentence but since we gonna perform Tokenization before this, we gonna lose some words that'd mess the sequence anyway. isnt that right?

Thank you so much sir😊🙏

Many Many Congratulations to you Sir for 10k Subs🥳🥳🥳

@hritikroshanmishra3630

3 ай бұрын

😁😁😁😁 182 k

well done buddy #nlp #nlptuts #nlpeasytuts

Very nice and very good start point. Can you pls suggest which text representation algo suited for log analysis.

Hello sir, I have had doubt on this topic how conversion is taking place, watch lots of video read lot's of blogs but no one can make me understand like u did. Hat's off to u keep up the great work.

Thank u sir .

You are a 💎.

thank you sir ji

i have one doubt can we normalize the vector engineering features? I think normalizing the vector will still contain the info that was previously their but in the lower scale for reducing computation. let me know if this is the correct approach

Feature extraction from text / text representation/ text vectorization - changing text to numbers so that model can understand Bag of words -

2 hours of pure diamond mine.

very nice explanation sir

Please make more videos on NLP !!!

Sir suppose length of sentences are unequal..... Tab kya padding ke alava aur koi option nahi hai in case of Tfidf Or ngrams etc?

Can you add RNN, LSTMs, and modern NLP using transformers!? Loved the content. Huge respect. Ps banjara market ka lamp! XD

Sir NLP series is really amazing, please recommend me best book for NLP because in few days I have an interview which will totally on NLP.

awesome

maza aya sir qasam sa

Hi Nitis sir, where can we get these notes in pdf format.so that it will be helpful while doing revision.

Thanks a lot sir .... Can you also upload a video on RNN & LSTM.

for tf idf, campusx term came 4 times but sir you considered it only thrice any reason for it? Anyway there we are getting +1 in realtime. Could you please reply me for this?

Sir please continue the playlist!!!!!

Thank you sir?

fr maza aagya ekdm

sir ji , removing stopwords took 3hours 26 min , tokenization karne mein ghabraahat c ho rhi hai

Hi Buddy, Great content! This video cleared all my doubts regarding BoW and TF IDF🙌 Are you going to take any NLP projects in future based on Machine Learning models?

@campusx-official

2 жыл бұрын

Yes

@mihirnaik3383

2 жыл бұрын

@@campusx-official Thank you!

@sidindian1982

Жыл бұрын

@@campusx-official Sir codes missing in the list ... BOW , TFIDF ..pls share

cv.fit_transform(df['eng']) How can we apply fit_transform on text? I think I do not understand this part

The example you gave for bigrams better than uni gram being able to differentiate the 2 sentences in vector space doesn't really make much sense to me, suppose instead of not I used a synonym of "very "instead like "extremely " then these 2 sentences should be similar in vector space but bigram model will say its different, so its actually not handling the word not rather just handling an unknown word differently

Where can I get these notes ?

Sir , i dont understand for idea of tf idf at 1:20:09. Since you said jo word document mein jyada hain but corpua mein kam hain. I confused in that way that how its possible. Since corpus mein to hoga hi hoga jyaga or equal.kindly clarify sir.

Sir will you make a video for nlp project....something good for resume..?

I have tried the assignment on kaggle if any one tried and want to discuss please let me know.

Many many congratulations for 10k sub. 🎊🎊🎊

@campusx-official

2 жыл бұрын

Thanks

@campusx-official

2 жыл бұрын

Thanks

best

Liked and shared your video. Subscribed your channel. What else can I do for you. You are doing a great job.

share the link for collab notebook

Sir, can you please share your code notebook?

why don't you keep the resource in the description, like the code link..

Thank you so much for such wonderful vedio. Sir Do u take any online classes as well?

@campusx-official

2 жыл бұрын

No, not right now

@campusx-official

2 жыл бұрын

No, not right now

23:00

How to join Mentorship program

1:23:40 - Campusx - word in IDF is repeated 4 times sir , .. Loge( 4/4) = 0

@Tusharchitrakar

3 ай бұрын

It's repeated only 3 times bro

sir please share the one note link

Bag of words minuets?

1:38:48

hi nitish sir, im faceing some problem with spell checker function def spell_correct(text): return TextBlob(text).correct().string it is taking so much on assignment dataframe, is there any fastest approach to check and correct spelling in log(n) times ?

@sidindian1982

Жыл бұрын

Run the file in google collab ,., because of GPU ... runs faster ...

Deep learning start Karo sir please 👍👍👍❤️

Please teach us BERT ALGORITHM

54:00

Please share this notebook source file to us !

You teaching method is good but you making it local only to Indian student not International for all to use. Please Make a new version of all your videos on NLP to English so everyone can learn from,🙏

40:34

when i perform bagofwords method like the video in kaggle notebook on the imdb data it says memory exceeded and just restarts the notebook :( what to do?

@user-qq7qi5kk5u

2 ай бұрын

same issue i tried in my machine but it said memory exceeded it need 18.1Gib after applying ohe

@forgotabhi

2 ай бұрын

@@user-qq7qi5kk5u guess we're poor lol

Sir please recommend some ML books

@campusx-official

2 жыл бұрын

kzread.info/dash/bejne/pXWuusGmdpvdd9I.html

Please complete NLP,Interview series and ML series

how can i get OneNote notes

@ritwiksingh4937

21 күн бұрын

by writing in ur notebook

Sir, please share the lectures python notebook file/

Sir, my question is: I have list of entities and a text.Like this: List=["Data Scientist", "Bihar", "Krishna"] Text=" I am Krishna. I am from Bihar . I want to be a Data Scientist" I want result like: "I am [Entity]Krishna[Entity]. I am from [Entity]Bihar[Entity] . I want to be a [Entity]Data Scientist[Entity]" Please help me with code to get this result.Thanx🙏

@priyaravind18

2 жыл бұрын

Did you get the code?

@kislaykrishna8918

2 жыл бұрын

@@priyaravind18 List=["Data Scientist", "Bihar", "Krishna"] text = ' I am Krishna. I am from Bihar. I want to be a Data Scientist' for entity in List: if entity in List: text = text.replace(entity,'[Entity]'+entity+'[Entity]') print(text)