What is Word2Vec? A Simple Explanation | Deep Learning Tutorial 41 (Tensorflow, Keras & Python)

A very simple explanation of word2vec. This video gives an intuitive understanding of how word2vec algorithm works and how it can generate accurate word embeddings for words such that you can do math with words (a famous example is king - man + woman = queen)

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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

[sanjeebkumargouda]

Great explanation .. 🙌🙌🙌 After watching many videos on this topic finally my understanding is cristal clear. You are doing awesome job sir.

[mehmetbakideniz]

I started searching wordtovec videos after failing to understand it by following NG's lessons. That is the single video that can actually tell that the word embeddings are 'the side effects' of the training process and this is how it finally clicked for me. Thank you very much!

[sunilgundrai]

As part of my NLP dissertation, I was looking for some real time use cases with some clear explanation. I found this a super useful and thank you for great demonstration with so many examples which are easy to understand. You rock with your teaching skills!!

[abir]

There's a subtle mistake in your CBOW explanation at 8:34 . In CBOW the target is always the central word based on context i.e the surrounding word . That means for a substring "Emperor ordered his" and window size of 3 the target is "ordered" and features are "Emperor, this"

[ahmedgamberli]

I like how you love your homeland and use it in all examples. Greetings and Love from Azerbaijan.

[vishaldas]

I think Dhaval, there is no non-linear activation function between the input layer and hidden layer. Correct me if I am wrong.

[ibrahemnasser]

What a mathematician would do when he/she hear you say "a vector is nothing but a set of numbers"

[vishaldas]

Also what would be your next topic in deep learning, is it sequence to sequence models?

[gayathrigirishnair]

This is the video that finally helped me grasp this concept. Thank You!

[ChaitraC]

Hello
I have doubt in this explanation, aren't all the weights gonna be same when our neural network is trained ?
what I mean is once we train a network W(T)X is what triggers a output node so how do we have different weights for every output word

[assafbotzer]

So clear, so eloquent, and so concise. Your contents are gift to this world. Thank you for using your intelligence, diligence and teaching skills to make a positive mark.

[pretomghosh]

This COBW and Skipgram is kind of encoding+decoding architecture like the autoencoders if I am not wrong?

[raom]

Presenting complex understand matter in an simplified way Dhaval Sir we you are an patience, consistent, simplified, organised way of subject presentation Explaination.

[yasaswinigollapally]

Sir your video is awesome 🙌, i have one doubt, what is the main difference between skip gram and bag of words model?

[yonahcitron]

incredible content. this guy is one of the best on youtube

[BeradinhoYilmaz]

is there standart real list for every onject given here. For example for cats, tails 0.2?

[ashwinivalmiki]

Hello sir,
Please make a video on GRE and IELTS preparation, this will be more useful and helpful to students like me planning to study Masters Abroad as your videos are clear, we get motivated .
Thank you.

[kmnm]

Hi Dhaval,
Great video on W2V, The link for the coding part of implementing Word2Vec in Python, please?

[harshvardhanagrawal]

Where do we get the predicted output from? How do we enter it for comparison?

[neerajashish]

Approximately how many videos are going to come in this series except the existing videos, by the way thanks a lot sir, the only playlist on youtube which was way more knowledgeable for machine learning and deep learning..