NLP Tutorial 1 – Spam Text Message Classification using NLP, sklearn | Natural Language Processing

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In this video, we will learn about spam text message classification using NLP. Natural Language Processing (NLP) is the field of Artificial Intelligence, where we analyze text using machine learning models. Text Classification, Spam Filters, Voice text messaging, Sentiment analysis, Spell or grammar check, Chatbot, Search Suggestion, Search Autocorrect, Automatic Review, Analysis system, Machine translation are the applications of NLP.

Tokenization is breaking the raw text into small chunks. Tokenization breaks the raw text into words, sentences called tokens. These tokens help in understanding the context or developing the model for the NLP. The tokenization helps in interpreting the meaning of the text by analyzing the sequence of the words.

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12:42 Installing packages
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32:05 Balance the data
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Gerard Alba Foz says:

Thanks for the video!

Sir, I get the problem of "lower case not found", and since I'm running it on VSCode, I can't call one single line, how to fix this?

Ousmane Traore says:

how to use uppercase in sms spam collection dataset ? How can I contact to you ?

Partha Paul says:

Hi Sir, can I use NLTK library?

Akash Chandra says:

Hello, how do you recommend I go through these videos?

Shivesh Sharma says:

Great tutorial sir πŸ‘πŸΌ
Sir can you write in comment the parameters if we use Multinomial Naive Bayes in place of RF with TFidf model in line clf.pipleline('tfidf',……….) it would be of great help if replied as soon as possible thank you sir

Sanket Zanwar says:

sir, the blogs are not accessible for NLP playlist.

Rahul Pandey says:

Bhai apka tutorial kamal ka hai, one of its kind

Abhishek Dubey says:

why we need to append the ham and spam ? need explaination

demo practice says:

please can you share spam.tsv file

Raju Pericherla says:

please share code for practice

Adarsh Gupta says:

Sir, the new NLP lectures have not been included in the playlist (18,19) . Please add those in this playlist , so that the students will have convenience to watch them all with a flow.

Anandan K says:

Is there possible to parse resume and get skills and College names etc

The Last One says:

thanks for your good explanation, but why you do not use the linear kernel for the SVM classifier because it is binary classification

Km Nm says:

Hi Laxmikant,
Excellent video tutorials on ML. I am amazed at the depth of your knowledge and of course the handson part. I have made it a point to complete each of your ML playlists. Thanks from KM

Tarun Tanwar says:

What an explanation!!! Thank god finally i found your link….Great job man! All the best

asim turi says:

Hello sir, I love your teaching and understanding method. When I go through your github profile. I am not able to find python or jupyter file for this video. I shall be thankful if you could share the link of this file here

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