Guys always remember : Tokens : is every word in a sentence Word: Token which is not stopword Stopword: Unwanted words ( should be removed but not all words . Words like not, ok should be avoided )
how to perform all these pre processing steps at a same time on a csv file containing data. and giving output in a new csv file. if someone knows how to do it. please share some resources/ references. its urgent.
@@utsavaggarwal_dsokay. I've tried data.ix but it's not working. i also tried data.loc and data.iloc but they both are also not working they are showing error. any other option regarding this or how solve this error please tell.
Hello, thank you so much for this video. But, when I got to the part of applying the preprocessing on my dataset, I keep getting the error 'method' object not iterable. Please how can I sold this
I appreciate your efforts! 🙏 Just a small off-topic question: 😅 I only have these words 🤔. (behave today finger ski upon boy assault summer exhaust beauty stereo over). How do I use this? 🤨
@@utsavaggarwal_ds i tried using ix, iloc and loc but still getting error. and yes pandas is also up to date. any other way to remove the error.? if possible provide solution fast, currently working on a project, but work is stopped due to this error.
Good tutorial But I got some error in the last code. data.ix[index,'Title'] = filter_sentence It says **AttributeError: 'DataFrame' object has no attribute 'ix'**
Hello Sir, When will you be updating the next video for chatbot. Your way of explaining is very simple and easy to grasp. Looking forward for the next video.
Stopwords trong NLP (Xử lý ngôn ngữ tự nhiên) là những từ xuất hiện rất thường xuyên trong ngôn ngữ nhưng ít mang ý nghĩa, chẳng hạn như "là," "và," "của" trong tiếng Việt hay "is," "the," "and" trong tiếng Anh. Chúng thường được loại bỏ trong quá trình xử lý văn bản để giảm độ phức tạp mà không ảnh hưởng nhiều đến nội dung chính của văn bản. Lemmatization trong NLP là quá trình chuyển đổi các từ về dạng gốc của chúng (lemma), giúp chuẩn hóa và giảm bớt các biến thể của từ. Khác với stemming, lemmatization dựa trên ngữ pháp và từ điển để tìm ra dạng cơ bản, chẳng hạn như "running" sẽ được chuyển thành "run," còn "better" sẽ được chuyển thành "good." Điều này giúp duy trì ý nghĩa chính xác hơn khi xử lý văn bản.
This video was extremely helpful to me, especially the last code cell. Thank you so much!
Guys always remember :
Tokens : is every word in a sentence
Word: Token which is not stopword
Stopword: Unwanted words ( should be removed but not all words . Words like not, ok should be avoided )
pro tip: you can watch movies at flixzone. I've been using it for watching all kinds of movies these days.
@Tristen Nasir definitely, been watching on flixzone} for since december myself =)
@Tristen Nasir yup, been watching on Flixzone} for months myself :D
It would be helpful if you could attach the code in the description
Good video . Jai Hind from Scotland.
Sir, i wanna say thanks because this video help me a lot for my thesis. thank you so much sir.
Well-explained! 👏👏👏
Good explanatory Video on data pre-processing and in very simple language.
Waiting for the next video.
how to perform all these pre processing steps at a same time on a csv file containing data. and giving output in a new csv file. if someone knows how to do it. please share some resources/ references. its urgent.
It's is applied in next videos
@@utsavaggarwal_dsokay.
I've tried data.ix but it's not working. i also tried data.loc and data.iloc but they both are also not working they are showing error. any other option regarding this or how solve this error please tell.
Best video on data pre processing. 😇
Glad you think so!
Hello, thank you so much for this video. But, when I got to the part of applying the preprocessing on my dataset, I keep getting the error 'method' object not iterable. Please how can I sold this
Thank you sir for this much simplistically explanation!, waiting for next videos...
Very simple explanation 👍
Very well Explained...
I appreciate your efforts! 🙏 Just a small off-topic question: 😅 I only have these words 🤔. (behave today finger ski upon boy assault summer exhaust beauty stereo over). How do I use this? 🤨
AttributeError: 'DataFrame' object has no attribute 'ix'
I got this error when I add ix attribute .kindly give me any solution
Use .loc function
@@utsavaggarwal_ds i tried using ix, iloc and loc but still getting error. and yes pandas is also up to date.
any other way to remove the error.? if possible provide solution fast, currently working on a project, but work is stopped due to this error.
@@KrishnaRamchandani have you solved your problem?
Good tutorial
But I got some error in the last code.
data.ix[index,'Title'] = filter_sentence
It says **AttributeError: 'DataFrame' object has no attribute 'ix'**
How to download all the results into csv
please upload the next videos of applying NLP technique to processed data in this video.
th-cam.com/video/8JcLENGoXL0/w-d-xo.html , @16:49
Nice Video,Please add the next video soon!
When will you release video to build chatbot
12:55 what does [0:10] mean in sentence data [Title] [0:10] ? need fast reply, thank you 🥹
How can i get this dataset , can you send it as a pdf file ?
Utsav , for single line the regex works , how it will work for entire column ? do we need to run for loop ?
Thanks in advance.!
Yeah run it on loop or use lambda function, it'll be simpler
where did ix come from please?
Amazing videos sir
Earned a sub
Very well explained
great 🤝
Thanks man 👍
Hello Sir, When will you be updating the next video for chatbot. Your way of explaining is very simple and easy to grasp. Looking forward for the next video.
Sir plz upload data set for preprocessing
Waiting for next videos in this section..
Plz...upload it sir.
Hey, What apps or web are you using to compile the code ?
good session
Why not do these all thing on data set why take simple example because there are some error when do with data set
Why your notebook is cutting from the left? bro improve first.
plz share source code
Stopwords trong NLP (Xử lý ngôn ngữ tự nhiên) là những từ xuất hiện rất thường xuyên trong ngôn ngữ nhưng ít mang ý nghĩa, chẳng hạn như "là," "và," "của" trong tiếng Việt hay "is," "the," "and" trong tiếng Anh. Chúng thường được loại bỏ trong quá trình xử lý văn bản để giảm độ phức tạp mà không ảnh hưởng nhiều đến nội dung chính của văn bản.
Lemmatization trong NLP là quá trình chuyển đổi các từ về dạng gốc của chúng (lemma), giúp chuẩn hóa và giảm bớt các biến thể của từ. Khác với stemming, lemmatization dựa trên ngữ pháp và từ điển để tìm ra dạng cơ bản, chẳng hạn như "running" sẽ được chuyển thành "run," còn "better" sẽ được chuyển thành "good." Điều này giúp duy trì ý nghĩa chính xác hơn khi xử lý văn bản.