Text Classification – Natural Language Processing With Python and NLTK p.11




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Now that we understand some of the basics of of natural language processing with the Python NLTK module, we’re ready to try out text classification. This is where we attempt to identify a body of text with some sort of label.

To start, we’re going to use some sort of binary label. Examples of this could be identifying text as spam or not, or, like what we’ll be doing, positive sentiment or negative sentiment.

Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1

sample code: http://pythonprogramming.net
http://hkinsley.com
https://twitter.com/sentdex
http://sentdex.com
http://seaofbtc.com

Source


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Comment List

  • sentdex
    November 17, 2020

    2020 batch Present sir

  • sentdex
    November 17, 2020

    what kind of variable types do I need in my for loop if I want to make my own categories and own file of word

    the double for loop is vague to me because I have no idea what fileid actually does

  • sentdex
    November 17, 2020

    That is kind of English Language.. Like Literally .. lol

  • sentdex
    November 17, 2020

    Make a video with the word2vec library please!

  • sentdex
    November 17, 2020

    can anyone explain why the neg category output wasn't printed ? Both the category words should've been printed as movie_reviews.categories has 2 categories pos and neg.

  • sentdex
    November 17, 2020

    Sir where to kept that file the document file

  • sentdex
    November 17, 2020

    sir may I ask what is the fileid for?

  • sentdex
    November 17, 2020

    Suppose if I have a directory of files and images and videos, using NLP i should train the model such that by passing a text message I have to access that file directly

  • sentdex
    November 17, 2020

    i have been programming for a few years now but i don't know how do i become an expert in the language. pls help

  • sentdex
    November 17, 2020

    Can you please tell us where do you learn all this stuff? It will be really helpful

  • sentdex
    November 17, 2020

    where is the positive and negative text files

  • sentdex
    November 17, 2020

    Great tutorials!
    I am trying to create a classifier similar to this one but using a labeled pandas data frame with WhatsApp messages, in place of the movie_reviews corpus. I am stuck on the step of creating this list you call documents (very important!). All I want to know is if this type of list would be possible from a dataset of labeled messages?

  • sentdex
    November 17, 2020

    Error := "FreqDist" pbject is not callable, please help

  • sentdex
    November 17, 2020

    so, please explain whaat is FreDist() working ?

  • sentdex
    November 17, 2020

    Can anyone explain how creating of list of common words, irrespective of classes, in the entire corpus would help as a feature?

  • sentdex
    November 17, 2020

    Can someone pls tell me. I am getting an error list object not callable 4:58. And moreover how is append function accepting two parameters?

  • sentdex
    November 17, 2020

    For those who are watching on 2019: Scikit has text feature extractor ready to use that includes TF-IDF.

  • sentdex
    November 17, 2020

    can i get a corpus for email classification.. like password reset rquest,customer enquiry mail,feedback mail,complaint mail…. sometime for this?

  • sentdex
    November 17, 2020

    Append Function has only a single argument?

  • sentdex
    November 17, 2020

    6:45 It's actually naive because it assumes all variables are independable :> <3 Love you Harrison!

  • sentdex
    November 17, 2020

    It was just awesome!Literally, Man!Great Work!

  • sentdex
    November 17, 2020

    This is an Amazing video! Everything well explained!

  • sentdex
    November 17, 2020

    Great, I think we can also use for multi class classifiaction, not only two class

  • sentdex
    November 17, 2020

    it has the word 'f*ck' 17 times

  • sentdex
    November 17, 2020

    I want to verify that a word provided by a user is a particular part of speech. Ex: user prompted to enter a noun; how do I use nltk to verify that word is a noun?

  • sentdex
    November 17, 2020

    First of all, I want to thank you for your great tutorial.
    I have Python 3.6.5 and when I call movie_reviews.words() function, it gives me an "AttributeError: can't set attribute".
    Could anybody help me about this? What should I do to resolve this problem?

  • sentdex
    November 17, 2020

    how to separate and count "positive" and "negative word" in a comment???

  • sentdex
    November 17, 2020

    Hi I have a question that i would like your expertise on

    Firstly i would like to say that your tutorial is great. It aided me a lot in my previous semester work. However i need some specific help.

    I am currently doing a project where i am basically collecting questions that are asked and generating various "tags" for each question. These tags allows analyst to understand what the context of the question is.

    So far i have thought about using topic modelling algorithm as well as pre processing methods that you have shared in your previous tutorial. What got me confused is how do we get the context of the question.

    For example the question "What is networking" is different when asked by someone majoring in Computer Science and someone who is in the business field! Any tips? I would greatly appreciate it hehe

  • sentdex
    November 17, 2020

    all_words actually has 39768 words 😛

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