at 37:38 i think the memory error is because you have a combined vocabulary of uni and bi gram which is obviously going to be huge , i think using just the bigram vocabulary by setting ngram_range=(2,2) will not cause this issue and your model will perform better
Thank you sir for these course. Each lecture from you is very comprehensive and easy to understand. Note: In between POS tagging lecture is not been uploaded. It was Chapter 4 as you said in the introduction video.
Nice Video Nitish Sir... Actually we are waiting for complete NLP playlist. We all know because of Mentorship Program you are too busy, but we just want roadmap of Deep learning for NLP. So we can move forward with NLP. Thank you ❤❤
Check in CZcams -- "KGP Taklie" , NLP playlist - LSTM for fake news vedio, concept & code is mentioned .... my rating is 5/5 for RNN you can to watch krish naik NLP playlist vedio (personally i hav'nt watched the vedio)..
Nice Video Nitish Sir... Actually we are waiting for complete NLP playlist. We all know because of Mentorship Program you are too busy, but we just want roadmap of Deep learning for NLP. So we can move forward with NLP. Thank you
1:04 - Plan of Attack 3:34 - What is Text Classification 5:38 - Types of Text Classification 7:34 - Applications 12:36 - The Pipeline 17:56 - Different Approaches 21:32 - Heuristic Approach 23:16 - Using API 27:14 - Using BoW and n-grams 38:58 - Using Tf-Idf 40:44 - Using Word2Vec 48:33 - Practical Advise
Very informative video. I am new to this field. Sir, as a business/data analyst we validate business rule where in we have some business rules. For now we use sql case to check the completeteness and validity of the business rule. But in future we want to create python code to run the business rule automatically on data to check validity and completeness. Why do we need this, as the business rules for the attribute keep on changing so we just want python code read the rule from server and just tell us the completeness and validity of the attribute. Our business rule are like (must be populated if account in (reatail, saving) and has a lenght of 9 digit). I hope this is possible using nlp. If you have any suggestion please reply
We are waiting for DL part Nitish Sir..Please make videos on how can we use DL for advanced DL.If this is not possible, please make roadmap so we can go with that. Thank you for efforts ❤❤
Great Job sir ..God bless you...webscrapping ,Tableau, Flask ,Python ye sb B tutorial kijiye ... HINGLISH TUTORIAL ME KHI NHI H..God bless sir to teaching well
Hi Nitish bhai ek video bnaado NER aur topic modelling pe bai bat complex topics hy sir k uprr se jata 😅😅 hy kuki ek interview merse ye poocha aur mei explain nhi kr paya dhngg se and got rejected its a request please🙏🙏
Sir, I have faced problem here while testing the model with first model then with second model . It s giving that the x_test features doesn't match the input features dimension . like 48k for i/p and 28k for test i/p. And the whole lecture is superb
Sir I have a small doubt It would be great help if you help me in that. I had strucked figuring it out. In word2vec we have 2 vector representation for a word. When word is center word we have one representation and when it is context word we have another representation. Why do we have two vectors?
Sir, the word "not" is also included in the english stopwords list. So do we need to first remove the word "not" from the stopwords list and then perform the stopwords removal step? OR is it fine to simply do the stopword removal as it for sentiment analysis? I have a doubt that the word "not" has the potential to disturb the accuracy of sentiment analysis task. Any Thoughts..?
Thank you for the amazing videos you are making and thanks for your efforts. I have 1 question, In your code X_train_bow = cv.fit_transform(X_train['review']).toarray() X_test_bow = cv.transform(X_test['review']).toarray() why cv.fit_transform and cv.transform differently used for train and test. I checked it changes the shape but what exactly is the reason. Kindly have a look at my question.
once we fit to the trainset,we will transform the testset using the vocabulary of trainset so that there is dimensional consistency while we input to the GNB model for prediction
How can we handle imbalanced data in case of Text classification? Maybe machine translation? Or replacing words in the minority classes with synonyms. Any other techniques?
X = [] for doc in tqdm(df['review'].values): X.append(document_vector(doc)) ValueError: need at least one array to concatenate while running this code for my whole dataset this error is coming can someone help
Hello Sir, please continue the playlist, Great/Best lectures! Anticipating second part of this text classification using Deep learning.
at 37:38 i think the memory error is because you have a combined vocabulary of uni and bi gram which is obviously going to be huge , i think using just the bigram vocabulary by setting ngram_range=(2,2) will not cause this issue and your model will perform better
Thank you sir for these course. Each lecture from you is very comprehensive and easy to understand.
Note:
In between POS tagging lecture is not been uploaded. It was Chapter 4 as you said in the introduction video.
you are the best teacher in this world sir best , teacher ever .........
Seriously i love ur explanation way..Dil se shukriya bhai aapko..lots of love and respect bhai apko❤🙌
sir mai fan hogya aapka mtlb ki mai wait krta hu jb bhi aapka koi naya lecture aata hai ,,i mean the way you teach is phenomenal....
Great lecture. I hope we will get to see the second part of this text classification using Deep learning.
Nice Video Nitish Sir... Actually we are waiting for complete NLP playlist.
We all know because of Mentorship Program you are too busy, but we just want roadmap of Deep learning for NLP.
So we can move forward with NLP.
Thank you ❤❤
Sir LSTM or RNN k videos bhi karo na upload, may be 50%+ logo ko deep learning phle se pta ho
Check in CZcams -- "KGP Taklie" , NLP playlist - LSTM for fake news vedio, concept & code is mentioned .... my rating is 5/5
for RNN you can to watch krish naik NLP playlist vedio (personally i hav'nt watched the vedio)..
Nice Video Nitish Sir... Actually we are waiting for complete NLP playlist.
We all know because of Mentorship Program you are too busy, but we just want roadmap of Deep learning for NLP.
So we can move forward with NLP.
Thank you
1:04 - Plan of Attack
3:34 - What is Text Classification
5:38 - Types of Text Classification
7:34 - Applications
12:36 - The Pipeline
17:56 - Different Approaches
21:32 - Heuristic Approach
23:16 - Using API
27:14 - Using BoW and n-grams
38:58 - Using Tf-Idf
40:44 - Using Word2Vec
48:33 - Practical Advise
Ok thanks
Hello plz make a video on text summarization..... extraction method.
IT WAS AMAZING!!! I LEARNED SO MUCH FROM JUST THIS ONE VIDEO OF YOURS. THANK YOU!!!
Very informative video. I am new to this field. Sir, as a business/data analyst we validate business rule where in we have some business rules. For now we use sql case to check the completeteness and validity of the business rule. But in future we want to create python code to run the business rule automatically on data to check validity and completeness. Why do we need this, as the business rules for the attribute keep on changing so we just want python code read the rule from server and just tell us the completeness and validity of the attribute. Our business rule are like (must be populated if account in (reatail, saving) and has a lenght of 9 digit). I hope this is possible using nlp. If you have any suggestion please reply
Sir, have you provided the "Deep Learning " version of text classification?
❤️❤️You are a great teacher
Very nice explanation sir 👏🥰
We are waiting for DL part Nitish Sir..Please make videos on how can we use DL for advanced DL.If this is not possible, please make roadmap so we can go with that.
Thank you for efforts ❤❤
Great Job sir ..God bless you...webscrapping ,Tableau, Flask ,Python ye sb B tutorial kijiye ... HINGLISH TUTORIAL ME KHI NHI H..God bless sir to teaching well
Sabke upar already hai. Check the channel
@@campusx-official web scraping ka link dena sir ...Mujhe nhi mila sorry sir
@@descendantsoftheheroes_660 czcams.com/video/8NOdgjC1988/video.html
@@campusx-official thanks sir love you 🤗🔥🔥
Hi Nitish bhai ek video bnaado NER aur topic modelling pe bai bat complex topics hy sir k uprr se jata 😅😅 hy kuki ek interview merse ye poocha aur mei explain nhi kr paya dhngg se and got rejected its a request please🙏🙏
Sir, I have faced problem here while testing the model with first model then with second model . It s giving that the x_test features doesn't match the input features dimension . like 48k for i/p and 28k for test i/p. And the whole lecture is superb
methods are actually different for test and train bow. cv.fit_transform for trainset and just cv.transform for testset.I too got trapped there.
Your videos are helping a lot.
Thanks a lot sir ji😀
How to do Multi Level Hierarchical Classification
Sir I have a small doubt It would be great help if you help me in that. I had strucked figuring it out. In word2vec we have 2 vector representation for a word. When word is center word we have one representation and when it is context word we have another representation. Why do we have two vectors?
Absolutely awesome video.
How I can contact with you
where i can find aws google news vector link?
you havent used the story variable anywhere, why did you calculate it?
Hi Sir! Is Accuracy , Confusion matrix sufficient to judge the NLP classification models? or any other techniques also exists?
F1 score , precision call must
bhai, Onenote pe likhne ke liye kya use karte ho? purchase link de sakte ho pls?
very informative .
Please upload deep learning approach wala video..
Sir, the word "not" is also included in the english stopwords list. So do we need to first remove the word "not" from the stopwords list and then perform the stopwords removal step? OR is it fine to simply do the stopword removal as it for sentiment analysis? I have a doubt that the word "not" has the potential to disturb the accuracy of sentiment analysis task. Any Thoughts..?
Depends on the application
i want to ask that what is the conclusion of result...it is showing accuracy of positive or negative reviews?
Sir ml playlist me aur video add kr do
If my sentiment column had multiple classes insted of binary, would LabelEncoder still work?
Nice Teaching sir
Done
Thank you for the amazing videos you are making and thanks for your efforts. I have 1 question, In your code
X_train_bow = cv.fit_transform(X_train['review']).toarray()
X_test_bow = cv.transform(X_test['review']).toarray()
why cv.fit_transform and cv.transform differently used for train and test. I checked it changes the shape but what exactly is the reason. Kindly have a look at my question.
once we fit to the trainset,we will transform the testset using the vocabulary of trainset so that there is dimensional consistency while we input to the GNB model for prediction
21:17 is the part 2 deep learning video out?
Sir PLZZ 🙏 upload video of xgboost and DBSCAN algorithm and anomaly detection in ml playlist PLZZ 🙏 Sir
How should we reach you ?? We wanted to have mentorship
LOVE YOU BRO...
Sir total kitne lecture hai NLP playlist me ?
4 aur
🔥🔥Thankyou sir
how to increase the accuracy please can u make a video on that
How can we handle imbalanced data in case of Text classification? Maybe machine translation? Or replacing words in the minority classes with synonyms. Any other techniques?
I usually do 'representative sampling'. You have a look at it.
33:26 When I'm getting attribute error on running that cv.fit_transform(X_train['review'])
I'm not even able to figure out, please help.
Simply do fit_transform X_train since review is not present in column , after use
thank you so much
Thanks Sir
sir please complete deep learning playlist please
24:23, 36:40
sir plz make a video on BERT . please
Plz share the link to the codes
Thank you sir
❤️
sir NLP series ka next video kyu nai aaraha?
Kyuki ml roadmap wala video banane me time nai mila. Iss week aa jaayega
Sir plz provide part 2
X = []
for doc in tqdm(df['review'].values):
X.append(document_vector(doc))
ValueError: need at least one array to concatenate
while running this code for my whole dataset this error is coming can someone help
Sir why do you make noises like chap-chup with tongue and nose. Its irritating.
4 min to bakchodi me waste kr di. Aise me views km ho jate h
Be polite sir. He is teaching quality content for free. He does not owe us anything,
you are our jeetu bhaiya !!