Build Text Classification Model using Word2Vec | Gensim | NLP | Python | Code

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Did excellent job ....thanx A lottt ...kindly do about Doc2vec as well....plz plzzzzz

nicely explained

God bless you for this. My question is, which of the methods of word2vec did you use. cBOW or Skip-gram. Also how do we implement the tf-idf averaging

❤ thanks for your sharing

hello Sir, What if I don't have label column and I want to make this task totally unsupervised?

great video, thank you so much.

hello! my project is about resume ranking,how can i use word2vec in my project,please reply.

Bro wv is not defined aisa error aa raha hain

Excellent information

Thank you. This helped me a lot.

Any idea how to work around this error:
ContentTooShortError: <urlopen error retrieval incomplete: got only 45501952 out of 109885004 bytes>

Getting this error when I run this code:
wv = api.load('glove-twitter-25')

Any help is much appreciated! Thanks!

Sir, please make a video on Creating a context vector from word vectors

Just wondering: isnt the sent_vec function wrong when it start ctr at 1? Shouldnt it start at 0 and then count up if words are in the wv?

This channel is a gem. How did I not find it before ?😔😔😔

The dataset isn't available.

lit explanation bro

hey Thank you Pradip!

would be great to compare tf-idf vs self trained word2vec,
Thanks again!