Word2Vec Part 2 | Implement word2vec in gensim | | Deep Learning Tutorial 42 with Python

[@codebasics]

Check out our premium machine learning course with 2 Industry projects: codebasics.io/courses/machine-learning-for-data-science-beginners-to-advanced

[@alishaparveen4735]

How we can apply multilabel classification after using Word2vec.

[@anandakhan4160]

i solved my problem. thanks.

[@ADESHKUMAR-yz2el]

the output made me WoW💯🔥 the beauty of Mathematics and genius brains thanks to all the engineers and scientists who really work hard fun fact : my keyboard suggesting the next word while i'm typing reminding me of word2vec🥰 these type of things motivates me to learn more about technologies

[@dopervigest7012]

The similarity output on "great" and "nice" is 0.69, Nice!

[@muskankhandelwal9555]

This playlist is really outstanding. The exercises are helping me a lot to remember the concept and practice it myself.

[@codebasics]

I am happy this was helpful to you.

[@namansethi1767]

Thank you sir for this playlist . This is the only playlist on You tube which clear my all doubts related to deep learning

[@codebasics]

Glad it was helpful!

[@assafbotzer7952]

Concise, eloquent and brilliant. Thank you 🙏

[@omharne1386]

This playlist is really outstanding. The exercises are helping me a lot to remember the concept and practice it myself.😀

[@poojapatila5233]

I was looking for this topic since many days, Finally gone through your video, Its awesome..................

[@codebasics]

Glad you liked it

[@MergiyaMelesse]

This playlist is really outstanding. The exercises are helping me a lot to remember the concept and practice it myself. Can you do for me part of speech tagging by transformer learning🥰🥰🥰

[@omarh.l.l8127]

You are such a great guy, amazing content. Well done!

[@sia-watsonlee]

i'm not sure if get it correctly , but our purpose was to achieve embedding words. and weights of the last layer of model had to be embedding vector. so lets say we want embedding vector for word 'king', how can we use this trained model to achieve that ?. i haven't seen an embedding part in this video or if i misunderstood something please tell me someone .

[@shadmanmartinpiyal4057]

I have the same question. Looks like this lecture shows how to build NLP model to find similar words for a given word.

[@shadmanmartinpiyal4057]

Any solution you found ?

[@shivam6565]

This is exactly what I was looking for. Thank you so much for the part 2.

[@loupa6128]

Hello, nice video. I want to ask some questions: Is gensim's Word2Vec purpose ONLY to create vectors that represent words? Also, can I use these vector representations to train a model for sentiment analysis? If yes, how?

[@testme2026]

This is guy is beyond awesome!

[@rajiv7]

Simply superb!!!

[@vihangafernando6644]

In this gensim word2vec model are you using continuous bag of words or skip-gram.

[@lydialiu7980]

Thank you! This is awesome! Could you pls share further the application after building this model in real production?

[@adithyabhat4770]

Awesome playlist, Thanks Dhuval!

[@codebasics]

Glad you liked it!

[@AshishKumar-ff5hc]

Sir plz try to complete this course as soon as possible 🙏🙏

[@bilalhassankhan221]

sir, there are 49 videos in your second channel I request you to please upload videos on python as soon as possible...

[@roberttuttle4284]

Thanks. This is great. One thing is that I am trying to get compare sentence to sentence, not word to word. So I want to know the similarity of the actual product reviews so that I can catagorize them. Maybe three catagories, Good, Bad, Neutral. I am wondering how I would do this.

[@codebasics]

Yea this is possible through sentence embeddings. Just look at the next set of videos in this playlist, we have covered it all

[@mdraihanulislamtomal6064]

how to apply SVM,NB,LR using W2V........ if u have made a video about this topic it may helpful. thanks

[@MasoudNazari-y8h]

Very useful. Thanks

[@shikhargoyal7494]

How can we incorporate 'Word2Vec' in an nlp model? Lets say I have table of reviews with a label stating helpful and not helpful. I need to create a prediction model, so how can i incorporate word2vec? please let me know

[@balaji-xu4tq]

Sir you have no idea how thankful I'm to you🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻🙏🏻

[@stwk8]

This is super helpful. Thank you for sharing

[@codebasics]

Glad it was helpful!

[@seenamosisa1404]

what you share is good but after I create the word2vec model how I can give for LSTM model please help me my aim is to classification news text

[@ananthmathreya2022]

I am not able to read the json file. When I try to read the file, it says permission denied

[@tomoki-v6o]

Thanks for the great explanation in the 1st video

[@codebasics]

Glad it was helpful!

[@fariyabano5995]

I am confused, how do we get numbers for our text in the end? I need to use those numbers in a prediction model

[@Reddie23]

Hello, thanks for the tutorial. How to load the model after you saved it?

[@shwetamishra8043]

Thankyouuu the content was very understandable

[@msmidhun8908]

could you please explain the model save procedure sir

[@chin4599]

It's helpful! Thank you so much!!

[@codebasics]

Glad it helped!

[@namrasshanavas6434]

Sir, you are just great!!

[@rakesh1889]

great explanation

[@faroukboome1904]

how can i print the embedding to all the reviewtext column .please respond

[@vipinsainilol]

Thank you for the video...

[@ramoushs]

amazing Video but I would like to ask after we find the similarity how can we extract the words

[@sadikaljarif9635]

so which method u follow here cbow or skip gram???

[@abdullahabrar8425]

Thank you very much, it was a great tutorial!

[@johnnysaikia2439]

This KZbin channel is in my hall of fame of AI

[@UMARUMAR-bl9bc]

Please how can one save the model as a txt file . Thanks

[@emmydistortion3997]

OMG! Thank You:)

[@bhanu0925]

Hi, do you have a playlist specific to NLP?

[@codebasics]

I am going to start that soon

[@punnarahul4068]

Can you please start tutorial on mlops so that your channel will be a care of address to machine learning?

[@usamahussain4461]

There is a curse... :) Nice video

[@rohanroy1756]

Question - when we use glove embeddings, we just download and use the vectors directly. But why in gensim word2vec, we need to train a model to our vocabulary? why cannot we use direclty? I am confused, please clarify.

[@pravallikaa3306]

Hi , did you get it?

[@sayakbhattacharya9188]

To get the context vector according to the semantics of the sentence

[@mihirpaghdal7974]

Sir I am facing error in installing levenshtein ERROR: Command errored out with exit status 1:

[@riddhisingla8789]

Hi Sir. Your content is amazing. When are you going to upload the next video and what topic you are going to cover in that?

[@kshitij_kaithal]

Awesome you are!

[@jatin7836]

Sir Ad daalo or paisa kmaao Huge fan and great content. Thank you for your videos.

[@abhinavkathuria3897]

Hello sir, great explanation. Sir can i use SVM and Linear Classifiers for multi class(Positive, Negative or Neutral) sentiment analysis? Please reply

[@619vijay]

Thanks a lot

[@schoolboylore9794]

THANK YOU SO MUCH

[@etherealshift9786]

TypeError: decoding to str: need a bytes-like object, float found how to solve this sir, I cannot proceeed. Please answer thank you :/

[@etherealshift9786]

--------------------------------------------------------------------------- TypeError Traceback (most recent call last) Input In [5], in () ----> 1 review.Text = df.reviewText.apply(gensim.utils.simple_preprocess) File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\series.py:4433, in Series.apply(self, func, convert_dtype, args, **kwargs) 4323 def apply( 4324 self, 4325 func: AggFuncType, (...) 4328 **kwargs, 4329 ) -> DataFrame | Series: 4330 """ 4331 Invoke function on values of Series. 4332 (...) 4431 dtype: float64 4432 """ -> 4433 return SeriesApply(self, func, convert_dtype, args, kwargs).apply() File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\apply.py:1088, in SeriesApply.apply(self) 1084 if isinstance(self.f, str): 1085 # if we are a string, try to dispatch 1086 return self.apply_str() -> 1088 return self.apply_standard() File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\core\apply.py:1143, in SeriesApply.apply_standard(self) 1137 values = obj.astype(object)._values 1138 # error: Argument 2 to "map_infer" has incompatible type 1139 # "Union[Callable[..., Any], str, List[Union[Callable[..., Any], str]], 1140 # Dict[Hashable, Union[Union[Callable[..., Any], str], 1141 # List[Union[Callable[..., Any], str]]]]]"; expected 1142 # "Callable[[Any], Any]" -> 1143 mapped = lib.map_infer( 1144 values, 1145 f, # type: ignore[arg-type] 1146 convert=self.convert_dtype, 1147 ) 1149 if len(mapped) and isinstance(mapped[0], ABCSeries): 1150 # GH#43986 Need to do list(mapped) in order to get treated as nested 1151 # See also GH#25959 regarding EA support 1152 return obj._constructor_expanddim(list(mapped), index=obj.index) File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\pandas\_libs\lib.pyx:2870, in pandas._libs.lib.map_infer() File ~\AppData\Local\Programs\Python\Python310\lib\site-packages\gensim\utils.py:311, in simple_preprocess(doc, deacc, min_len, max_len) 288 def simple_preprocess(doc, deacc=False, min_len=2, max_len=15): 289 """Convert a document into a list of lowercase tokens, ignoring tokens that are too short or too long. 290 291 Uses :func:`~gensim.utils.tokenize` internally. (...) 308 309 """ 310 tokens = [ --> 311 token for token in tokenize(doc, lower=True, deacc=deacc, errors='ignore') 312 if min_len 365 return str(text, encoding, errors=errors) TypeError: decoding to str: need a bytes-like object, float found

[@its_kumar]

Great Video!!

[@divyavuddagiri5877]

Rnn(lstm) and word2vec model is equal or not

[@debatradas9268]

thank you so much

[@engineeringtalk5926]

Sir please make video on transformer model

[@aditigupta3202]

AttributeError: module 'gensim.utils' has no attribute 'simple' Can someone tell what to do in this case?

[@akshay-g2p]

use only simple.preprocess without using parenthesis ,and make sure that ,your dataset dont have any null value use:-df.(column_name).apply(gensim.utils.simple_preprocess) dont use "()"

[@sirik6973]

Hii sir, I was selected in infosys and tcs, could you please tell me which one I can choose so that I can get a onsite opportunity .I really want to work in states mostly, it's my dream.I am now in 4th year cse from india.

[@goumuk]

tcs

[@nikhilgupta4859]

How to use it in classification task?

[@GautamKumarBEE]

Add 5-6 more videos quickly please. A lot of my friends are following it and would loose the rythm if videos doesn't come on time.

[@codebasics]

Sure Gautam, I will look into this.

[@kushalneo]

Please add GitHub link to ipython notebook.

[@thepresistence5935]

You didn't showed the vector representation

[@Rajkumar-vc2pg]

How can i use this model to train and fit in any machine learning algorithm ?? Like decision trees? If anyone knows can share me article or blog... I want to understand how we use in training a ml model . I tried like making a dictionary like {word: vec} and converted words in sentence in to vec and trained but it isn't effective.

[@Ahmet-vb6nf]

Thanks

[@markstevenesteves9504]

ModuleNotFoundError: No module named 'panda' please help me to fix this

[@umerfarooque6373]

Pip install pandas

[@hanishtangella413]

where and how to unzip that json file ..someone please help

[@날개달린_양]

Love you

[@pulsereality806]

oh no I don't want my computer to burn🤣🤣

[@tsaibro]

nice love you

[@prajwalbk5725]

"great and iphone, see similarity score is very less its working perfectly". Not a iphone fan lol

[@BISONTECH]

خدا خیرت بده

[@datasciencegyan5145]

🤣system will burn if u check the solution before solving it

[@paulowiz]

Where is the code?

[@codebasics]

Please check video description. You will find a link of my GitHub page that has all resources

[@paulowiz]

@@codebasics Thanks a lot =)

[@muratozmen7307]

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At first, everyone did not believe in Bitcoin, then in Defi, then in NFT, and now someone really does not believe in the RJVX13 algorithm :D

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You guys are so funny, read about the RJVX13 algorithm and the FBC fund

[@dogukanuz9528]

Yes Yes! Read everything, and then say that you did not know RJVX13 algorithm!

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Everyone went crazy with ICO, then with Defi, then with NFT, now everyone is going crazy with the RJVX13 algorithm

[@batuhankaya3448]

just google RJVX13 algorithm and don't worry

[@elifkacar3212]

Why worry about cryptocurrency quotes if there is RJVX13 algorithm?

[@Alpere_ced]

RJVX13 algorithm is my choice, i dont worry about BTC rates at all

[@sonsaniye2417]

First there was an ICO boom, then Defi, then NFT, and now everyone is crazy about RJVX13 algorithm

[@flipsch]

is there really still a person who does not know about the existence of RJVX13 algorithm?

[@ets2jetciler586]

RJVX13 bring me 300% profit because of Tesla pump

[@sarasmith1647]

Hello I want to apply it to arwiki-20180120-pages-article-multistream.xml.bz2 can you plz help me how to use this file