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Articles in the Natural Language Processing (NLP) Category

Natural Language Processing (NLP), Python »

[19 Feb 2018 | No Comment]

This article shows how you can use the default Stopwords corpus present in Natural Language Toolkit (NLTK).
To use stopwords corpus, you have to download it first using the NLTK downloader. In my previous article on Introduction to NLP & NLTK, I have written about downloading and basic usage example of different NLTK corpus data.

Natural Language Processing (NLP), Python »

[12 Feb 2018 | No Comment]

Natural Language Processing (NLP) is about the processing of natural language by computer. It’s about making computer/machine understand about natural language. Natural language means the language that humans speak and understand.
Natural Language Toolkit (NLTK) is a suite of Python libraries for Natural Language Processing (NLP). NLTK contains different text processing libraries for classification, tokenization, stemming, tagging, parsing, etc.

Machine Learning, Natural Language Processing (NLP), Recommender System, Sentiment Analysis »

[28 Mar 2017 | Comments Off on Guide to Recommender System research containing Sentiment Analysis & Machine Learning]

Below is the step-by-step beginner guide to conduct experiment on any Recommender System research that contains some work on Natural Language Processing (NLP) as well. So, this can be a guide to NLP research work as well specifically for Sentiment Analysis. Recommender System research can include users’ reviews text and process them using Sentiment Analysis & Machine Learning techniques.
Before starting the research on Recommender Systems or NLP experiment with data, we should be very clear about the things highlighted below. If these things are understood properly then it will be …

Machine Learning, Natural Language Processing (NLP), Python, Sentiment Analysis »

[25 Jan 2016 | 2 Comments]

This article deals with using different feature sets to train three different classifiers [Naive Bayes Classifier, Maximum Entropy (MaxEnt) Classifier, and Support Vector Machine (SVM) Classifier].
Bag of Words, Stopword Filtering and Bigram Collocations methods are used for feature set generation.