Word2Vec Simplified|Word2Vec explained in simple language|CBOW and Skipgrm methods in word2vec

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Word2Vec Simplified|Word2Vec explained in simple language|CBOW and Skipgrm methods in word2vec
#Word2Vec #UnfoldDataScience
Hello All,
Welcome to Unfold data science RU-vid channel. My name is Aman and I am a data scientist.
About this video:
In this video, I explain the word2vec concept in detail. In this video, I talk about how Word2Vec works using skipgram and CBOW methods. I also explain how internally word embedding works and what are the benefits of word embedding. I explain in detail how embedding takes place and why it is so important in Natural language processing.Below questions are answered in this video:
1. How Word2vec works using skip gram and CBOW
2. What is Word2Vec
3. What is word embedding
4. Methods of word embedding
5. Continuous bag of words in Word2Vec
6. Skipgram in Word2Vec
About Unfold Data science: This channel is to help people understand basics of data science through simple examples in easy way. Anybody without having prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at high level through this channel. The videos uploaded will not be very technical in nature and hence it can be easily grasped by viewers from different background as well.
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Опубликовано:

8 июл 2020

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Комментарии : 151

@abdullahilawal3220 3 года назад

Masha ALLAH, i have searched for three years to get a simple explanation of w2v until i found your video today. U have done a great job. Thanks alot

@UnfoldDataScience 3 года назад

Your comment made my day Abdullahi. thanks for such motivation. keep watching.

@debbs_io 2 месяца назад

Finally a simple, clear and complete explanation of this word embeddings. Thank you so much. I've studied and searched for months and you've just made the whole thing clear and straight forward.

@victorsolomonmachinelearning 2 года назад

I've been searching for a comprehensive explanation without the technical jargons. you are the best teacher

@UnfoldDataScience 2 года назад

Thanks Solomon.

@metalhamster14 Год назад

You have a gift. A natural teacher.

@SaHaRaSquad Год назад

Finally an understandable explanation of how those methods work. Short and to the point, thanks for this video.

@LocksRevenge 6 месяцев назад

Simplified and concise, Thank you Sir.

@SallyMwalrMusic Месяц назад

Just sending love and regards seem like a good person and appreciating your efforts to teach others,

@fatemeazizi2224 Год назад

simply explained, Thank you

@unexpected2004 3 года назад

Great stuff! Couldn't find a better video with such well assembled content.

@UnfoldDataScience 3 года назад

Glad it was helpful!

@RohanPaul-AI 3 года назад

As always, superbly simple and great explanation. Many thanks.

@UnfoldDataScience 3 года назад

Welcome Rohan.

@bekiofficialchannel9746 Год назад

Thank you! I got the basic concepts about word2vec.

@nikitasharma4957 2 года назад

Jaise hi word or vector m difference smjh aaya i 👍 ❤️ like it seriously..after that I HV seen full vedio..osam explanation

@mrdh927 3 года назад

Thank you, Aman, I really appreciate your simple explanation.

@UnfoldDataScience 3 года назад

Most Welcome. Your comments are precious for me.

@vittalhundarad1644 Год назад

thank you sir , nice explanation

@findyourpassion1677 3 года назад

Very helpful explanation. Looking forward to seeing more. Thanks in advance.

@UnfoldDataScience 3 года назад

Glad it was helpful!

@vaishnavibhosale2272 Год назад

great work 👍👍

@henriquemaulerborges1390 2 года назад

You video is very simple to undestand, thank you man!

@UnfoldDataScience 2 года назад

Welcome

@SACHINKUMAR-zo5pm Год назад

I find ur videos very helpful, many topics which are not explained well in other channels, i come to ur channel to see if it is available and u have never disappointed me. Keep up the good work. Thanks.

@UnfoldDataScience Год назад

Thanks Sachin. Please share with friends also

@mahikhan5716 Год назад

great aman . tactics of ur teaching is really tremendous

@arcanepersona1676 Год назад

May Allah increase your knowledge my friend, i am just starting with NLP and you help me learn the basics well. I didnt know what one hot embedding means. Thanks and keep it up. Also could you please do a project end to end in NLP for example sentiment analysis ? I want to see these techniques in real action. Thanks again :)

@NightSurge. 2 года назад

Great video, straight to the point and easy to understand.

@UnfoldDataScience 2 года назад

Cheers.

@AbhishekKumar-hh5oh 3 года назад

well explained and in a simplified way. Thanks a lot for this video

@UnfoldDataScience 3 года назад

Glad it was helpful Abhishek.

@krishnabhadke6161 2 года назад

Perfectly Explained , hats off to u!! Thank You

@UnfoldDataScience 2 года назад

You're most welcome

@exuberantyouth8765 Год назад

Thanks Aman

@piyalikarmakar5979 2 года назад

Thank you so much sir.. From the documentations I was confused.. Thanks a lot for such cleared and easy explanation..

@UnfoldDataScience 2 года назад

Welcome Piyali.

@ShahzadKhan-zq9ty 3 года назад

one of the finest explanation, thanks bro

@UnfoldDataScience 3 года назад

Thank u.

@jialaiz9101 3 года назад

Very intuitive, thx man

@UnfoldDataScience 3 года назад

welcome Jialai.

@vijaym4598 2 года назад

Very simplified about Wrod2vec....Thanks and all the best

@UnfoldDataScience 2 года назад

Glad you liked it

@sandipansarkar9211 2 года назад

finished watching

@gurmindersinghmalhotra8184 2 года назад

Aman bhai, thanks for excellent explanation.

@UnfoldDataScience 2 года назад

Always welcome Gurminder Bhai.

@pankajuprety9216 3 года назад

your explanation is simple clear and best

@UnfoldDataScience 3 года назад

Thanks Pankaj.

@udayradhe6537 Год назад

Amazing! so well explained in simple terms.

@UnfoldDataScience Год назад

Thanks Uday

@learn-and-live 2 года назад

thank you for this clear explanation!

@UnfoldDataScience 2 года назад

Thank you

@suhanshupatel9204 3 года назад

Thanku bhaiyya.

@UnfoldDataScience 3 года назад

Welcome Suhanshu.

@uwaisahamedimad556 Год назад

I have written the same in one of your previously watched video,but still I want to write it...You are really unfolding Data Science.

@UnfoldDataScience Год назад

Thanks Uwais. Your words mean a lot.

@aniketwagh570 2 года назад

awesome video sir, really awesome.

@UnfoldDataScience 2 года назад

So nice of you Aniket. Your comments are precious for me.

@ribamarsantarosa4465 9 месяцев назад

humble and nice presentation :)

@UnfoldDataScience 9 месяцев назад

Thanks a lot.

@shivnathsinghgaur5972 2 года назад

i spend too much time to get logic behind woed2vec but now i am satisfy

@UnfoldDataScience 2 года назад

Thanks for watching.

@sunilupadhyay7948 3 года назад

very informatics pls continue.

@UnfoldDataScience 3 года назад

Thank you Sunil, I will

@sharatchandra2045 3 года назад

good and simple explaanation

@UnfoldDataScience 3 года назад

Thanks for liking Sharat.

@juniormedjeufopa3780 3 года назад

Thanks :) Great explanations

@UnfoldDataScience 3 года назад

Welcome.

@LearningWithFun333 2 года назад

Great explanation. thanks a lot.

@UnfoldDataScience 2 года назад

You are welcome! Tabassum.

@caoilim 2 года назад

I really don't comment but this is just great. Really helped me out with my college assignment. I was tearing my hair out before this. Genuinely thank you.

@UnfoldDataScience 2 года назад

Glad it helped!

@karthickd537 2 года назад

Very nicely explained in a very simple way.

@UnfoldDataScience 2 года назад

Thanks Karthick.

@RezoanurRahman 2 года назад

Literally can not make it more simpler than this.

@UnfoldDataScience 2 года назад

Thanks a lot Rahman.

@smartrider.strider 3 года назад

Great stuff!

@UnfoldDataScience 3 года назад

Thanks Aditya.

@the_street_coder4433 3 года назад

Owosome Men, I Loved the explanation.

@UnfoldDataScience 3 года назад

Glad you liked it

@preranatiwary7690 3 года назад

Good one again!

@UnfoldDataScience 3 года назад

Thanks again! Happy Learning!

@omkarjadhav13 3 года назад

Good work.

@UnfoldDataScience 3 года назад

Thank you Omkar.

@pranjalgupta9427 2 года назад

Nice explanation

@UnfoldDataScience 2 года назад

Keep watching Pranjal.

@user-yy9vt2np7k Год назад

thank you!

@UnfoldDataScience Год назад

You're welcome!

@linxin3811 3 года назад

Very good introduction to Word2Vec. Would have preferred a bigger writing space, but nonetheless was very clear

@UnfoldDataScience 3 года назад

Glad it was helpful Kevin.

@RaghavaIndra 3 года назад

Very good explanation!

@UnfoldDataScience 3 года назад

Thanks Raghava.

@rejithmadhavan5735 Год назад

Precise explanation. Very useful. Thank you Aman. Just one suggestion, visually it will be more soothing if you could follow straight line on your whiteboard.

@UnfoldDataScience Год назад

Thanks a lot for suggestion.

@sudiptamang1018 2 года назад

thank you

@UnfoldDataScience 2 года назад

You're welcome Sudip.

@sandipansarkar9211 3 года назад

great explanation

@UnfoldDataScience 3 года назад

Thanks Sandipan.

@syedharis3235 3 года назад

Great job bro!

@UnfoldDataScience 3 года назад

Thanks for the visit Syed.

@dhlpaket2247 3 года назад

Best man

@UnfoldDataScience 3 года назад

Thanks again.

@pakistantechknowledge3911 2 года назад

you mean sparse vector of word will give dense vector. how features are selected and how values are assigned ?

@anurodhchoudhary1689 3 года назад

when Legends start to teach everything becomes ezzzz!!!!!

@UnfoldDataScience 3 года назад

Thanks Anurodh.

@claudeclaude9991 2 года назад

Man, you are great. Thanks a lot. Do you have any doc2vec video or playlist?

@UnfoldDataScience 2 года назад

Thanks a lot, doc2vec, I will create. Have not created yet.

@omarwaleedsalihalrassam905 3 года назад

Great explanation and well done, my question is how the numbers can be selected to set the features? I mean, in your example at time (5:00) of your video, you assigned 0.9 to the apple and 0.85 to mango ..etc, how these numbers can be assigned?

@UnfoldDataScience 3 года назад

We do not assign manually, framework assigns.

@shaheenullah3212 3 года назад

Great sir. please sir also share about pos tagging using this approach

@UnfoldDataScience 3 года назад

Sure, will do Shaheen.

@saqibcs 2 года назад

Brother, great explanation. I will appreciate if could just tell where I can found next video

@UnfoldDataScience 2 года назад

Please check in my playlist for NLP

@binaykumar1616 2 года назад

You explained nicely. Please use a bigger screen.

@UnfoldDataScience 2 года назад

Thanks for watching and Feedback Binay.

@prashanthkolaneru3178 3 года назад

great stuff, where this application mostly used?

@UnfoldDataScience 3 года назад

Thanks Prashanth, in many NLP application where we need to capture semantic meaning of sentence.

@SibanandaPattanaik Год назад

@Unfold Data Science In the starting whatever encoding ur doing, I don't think it is one hot encoding instead it's a BOW representation...Correct me if i m wrong.

@UnfoldDataScience Год назад

wil check

@aqsashahzad5139 3 года назад

Informative video... (y) Or in m sy best algorithm konsa h text classification tasks k liy cbow ya skip gram?

@UnfoldDataScience 3 года назад

Depends on what kind of data you are working for.

@piyalikarmakar5979 2 года назад

Sir, I have one query that as input we need to feed the one hot representation of the surrounding words including the one hot vector of the target word or excluding so?

@UnfoldDataScience 2 года назад

Hi Piyali. Excluding. For target you might need to do separate encoding.

@piyalikarmakar5979 2 года назад

@@UnfoldDataScience okay sir..then in case of getting all the word embeddings of the input sentence..one hot encode of the words under the window passed through CBOW and find the middle target word using the feature based information.. then slide the window and repeat the same untill the end... is it the process sir?

@suriebc6779 3 года назад

Hi, I have an experience of 8 years in IT(Programming) and started preparing for data science career transition. My query is How can I put up in Resume. Shall I tell them that, I am new to this and Know all the concept and worked on kaggle datasets? Will they allow or reject since no past experience on data science? looking forward for your valuable comments.

@UnfoldDataScience 3 года назад

Hi, The query needs some bit of understanding your profile and giving suggestion I see you are looking for some career guidance, If yes, you can reach me directly for one on one mentorship. You can go to "About" section in the channel and click the link "One to One Mentorship Link"

@nagithareddy1798 2 года назад

How to write a program to implement continuous bag of words model using knn algorithm (using python).

@UnfoldDataScience 2 года назад

Hi Nagitha, You can convert word to number and run KNN.

@nagithareddy1798 2 года назад

@@UnfoldDataScience could u please tell in detail I'm new to this course I donno how to do if possible please provide the code with explanation

@omarsalam7586 Год назад

@mahikhan5716 Год назад

i have one question since bag of words has issue so isn't it used anywhere ?

@UnfoldDataScience Год назад

Mostly not used as it's very simple technique

@maYYidtS 3 года назад

bro how can we decide vector space size ex. (5000 words*300 vectors)...here 5000 is our vocab size, but how can we decide the 300 lengths...

@UnfoldDataScience 3 года назад

Normally we take 300 dimension however if our vocab size is huge, then processing might be difficult with more number of dimension hence we try limiting it to 200 or so. If you do not have infra issue, you can go for 500 or even more.

@maYYidtS 3 года назад

@@UnfoldDataScience Thanks....bro

@maYYidtS 3 года назад

@@UnfoldDataScience so it is considered as a hyperparameter?...can we change this in tunning. and please make video on optuna, biasen hyperparameter tunnign.