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In this playlist we will be discussing about the Tokenization process in the Natural Language Processing which is the basic step in any NLP use case.

#NLP #Tokenization

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Udhhav Arora says:

Just completed this playlist!
Can you please make a video on Text Classification, BERT and Named Entity Recognition!!

Sandipan Sarkar says:

Very good video Krish. Near to clear my basics about NLP by watching and simultaneously practising on these free videos. Thanks

Teetan Robotics says:

please order nlp playlist

Deepak Srinivasula says:

I am starting to take this course now to learn NLP for my project
I have no background knowledge in ML. Is it okay to proceed without ML knowledge?
I have a good grasp on python though

Thanks in advance 🙂

Neuraldata says:

I appreciate your work Krish ❣️

jalla Aswini says:

Hi sir, Your explanation is good. Please make a playlist on more advanced NLP topics


Please make more videos on transfer learning and training neural network using pre-trained models.
Thanks . More power to you.

Yared Dessalegne says:

Hello sir, how to labled Nlp dataset that means how to assigned target value for our text corpus to train for deep learning , for example my target values OR outputs are:

1, Subject -verb error

2, Object -verb error

3, Adverb verb agreement error

4, Word-sequence agreement error

5, correct

Nasik Sami says:

is the series complete or there will be more videos on NLP?

Krishna Mishra says:

Sir please make video on Latent Dirichlet Allocation, Latent Semantic Analysis & non-negative matrix factorisation, these are topic Modelling technique

Vaibhav Sharma says:

This video lecture is not download friendly. The video cannot be played at 2x speed or played in the background.

muhammad zubair Baloch says:

Sir Named Entity Recognition per aik video banain

Megha Choudhary says:

Hi Krish, could you please make more videos on NLP like spacy, ELMo ,BERT

Raviteja Gudla says:

@KriSh Could you please share good book for NLP..

Rajsekhar Reddy says:


Could you please post videos on word2vec, skipgram, cbow,glove, word embeddings

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